Building Your Customer Base

Customer acquisition is difficult for any business. In fact, many studies have found that it is five times more difficult to acquire a new customer than to obtain an existing one.

As the digital world keeps evolving, the way consumers ingest and use information has changed – particularly in the way they shop and interact with new brands.

As a result of these shifts, acquisition strategies have evolved as well. 

In today’s digital environment, successful customer acquisition strategies necessitate the proper execution of these three core strategies:

1. Calculate Customer Value 

A chief component of customer acquisition is to not just seek to acquire any customer at all, but rather the ones with highest projected lifetime value (LTV). 

For instance, if every customer you bring is a one-time buyer who never comes back after the first purchase, then you will have no recurring revenue. As a result, the return on advertising spend (ROAS) from your acquisition campaigns as a whole will be negative.

The truth is, the highest value customers – also known as most valuable buyers (MVBs) – who spend more, more often than the rest of your customer base are the ones who wind up driving the bulk of your revenue.

Below are ways to determine a new customer’s potential value. Ultimately, the ones who fall within the upper tier will be the most receptive to special, personalized dialogues designed to cultivate new relationships and stimulate further purchases down the road.

Understand the Acquisition Source

Oftentimes, the future lifetime value (FLTV) of customers correlate with the channel or media source that they were funneled through and/or as the type of message or call to action (CTA) that they responded to.

For example, a customer acquired through a sale offer on social media would generally have a lower FLTV than another who came through organic search. This is because the latter was likely actively seeking you out in the first place.

Paid Search and Social Media Analysis

When utilizing paid search via a search engine like Google for customer acquisition, you are granted access to a comprehensive overview of search terms tied to both your products and the types of customers that each one funnelled into your brand.

Equipped with this information, you can allocate priority to certain search terms by assessing which ones drew in the customers who demonstrated higher levels of value.

2. Identify Which Outreach Efforts Work (and Which Don’t) 

Targeted acquisition requires a keen understanding of not just your customer universe, but the different segments that you are marketing to. 

Along the way, you will find that certain messages and offers resonate more with certain segments. Therefore, pinpoint the chief segments (also known as customer personas) to hone in on and spend more of your resources working to bring them into the fold.

The most effective acquisition campaigns are the ones that maintain a close eye on promotion history and conversion rate in order to show how efficiently your advertising dollars are being spent. This affords you the ability to adjust your allowable advertising budgets and increase efficiency across the board.

“Half of the money I spend on advertising is wasted. The trouble is, I don’t know which half.” – John Wanamaker

Gone are the days when marketers – even pioneers like Wanamaker – could not attribute their customer acquisition campaigns to certain campaigns or creatives. These days, you have all of the technology and data at your disposal to help you understand both the efforts that are working and the ones that are not. 

From there, you can realign your focus to better match the messages and channels that are showing the greatest conversion rates and return on investment (ROI).

Employ Omnichannel Marketing

The most effective and efficient acquisition campaigns are implemented across multiple channels using a multitude of data through analytics software.

If you reach someone through multiple channels, there are likely synergies that exceed the sum of the parts. In turn, make use of the channels that are most relevant to each customer and craft timely, relevant messages across each one to maximize their chances of conversion.

3. Leverage Automation Tools

The timeframe of openings to reach customers has changed dramatically in the digital age. Given the way people shop today, you must be able to respond to both their inquiries and behaviors almost instantaneously. 

The fact is, there are almost countless amounts of buying options that can be executed with a mere finger swipe or click of a button. When combined with a vast sea of competitors vying for their attention, consumers have become more fickle than ever.

Modern marketing automation software can help calculate how much you are allowed to spend in order to acquire each customer. This is known as an acquisition allowable (or allowable acquisition cost) – which is gauged by projected LTV, ROAS, channel, and offer.

In turn, Predictive Marketing Automation (PMA) platforms are more necessary than ever in order to stay on top of who is interacting with your brand, take advantage of high-value opportunities when they arise in real time, and modify your acquisition efforts to help meet (and ultimately exceed) your benchmarks and goals.

Omnichannel Success

In this omnichannel age of marketing, multiple impressions across channels not only heighten your brand awareness, they increase your likelihood of sales and conversions. 

The proper combination of email and direct mail serves as an excellent example of this principle, and is well worth taking the time to both understand and implement. 

While each channel has its own respective core strengths and weaknesses, many marketers don’t take advantage of the fact that they can actually synergize and supplement one another when used in tandem.

Here are five ways that fusing email with direct mail can help your business increase ROI and drive profits:

Re-Engage Non-Responders

While email is cheaper to send and can be easily automated, the average person is overwhelmed by so many emails each day. Therefore, most emails wind up ignored, sent to the trash bin, or simply forgotten – resulting in no further response or engagement.

Direct mail, on the other hand, achieves much higher open and response rates than email. Most people still read the physical mail that they receive, even if they are ultimately disposed of. 

If you have a key message that simply isn’t being read via repeated emails, you can easily create a list of those not responding to your emails, and use their information to craft a highly-personalized and targeted direct mail piece. This personal touch can help you to reach members of you base that likely would not have returned otherwise.

Reach Out to Prospects for New Customer Acquisition [PURLs]

It is generally frowned upon (and in some places punishable by law) to send emails to prospective customers without their consent. However, initial acquisition efforts via direct mail does not pose the same issues, and you can use your direct mail message to direct potential customers to a personal landing page – also known as PURLs.

PURLs usually include a recipient’s name in the web address. Including PURLs allow you to generate actionable data from those who engage with your direct mail efforts. You can also use QR codes, loyalty discounts, and single-use redeemable coupons to help increase engagement across digital channels.

PURLs also give marketers the ability to measure response and conversion rates for a direct mail campaign and create custom audiences in order to retarget them later.

In addition, PURLs can help you measure and retarget your direct mail recipients. If you invest in PURL tracking software, you can use the results to help inform future marketing campaigns.

Complementary Campaigns

When combined together, both email and direct mail can be designed in a way that they complement one another.

The following three statements are based upon the old adage of 1+1=3:

• If you send an email, you’ll get one sale. 
• If you send a catalog, you’ll get one sale. 
• If you send both simultaneously, you’ll get three sales.

Simply put, combining email and direct mail can offer an extremely effective one-two punch and bring in sales that would not have been possible through either channel alone. 

With so much competition in the retail and e-commerce sphere, it is more necessary than ever to find ways to stand out, carve your own footprint, and maximize ROI from your campaigns. Getting the most out of each channel is essential in omnichannel marketing, so you might as well use one to supplement the other.

Discounts Driving Profits

One of the most effective methods retailers use to boost sales and customer engagement is by offering discounts on their products.

In fact, a Software Advice study found that discounting is the most popular retail pricing strategy of all, with 97 percent of survey respondents stating that they utilize discount pricing.

However, without a carefully calculated discount plan in place, you could actually wind up slashing profits, bringing in too many low-value buyers, and even hurting your brand integrity.

Therefore, it is imperative to know how to implement a discount strategy the right way. This guide will shed light on the key discounting tactics that will put your business in the best position to increase transactions and grow your customer base.

1. Set Goals: What Should Discounting Accomplish?

Prior to choosing your discount strategy, make sure that your end goal is clearly defined. Some examples include:

Customer Acquisition

Discounts are a great way to incentivize consumers who have never bought from your brand before. With less to lose on their end, they’re more likely to give your products a shot. Plus, if they’re satisfied with their purchase, they’re officially on your radar and are more likely to purchase again.

Limited time and/or storewide offers are also particularly effective in this case. Adding a sense of urgency serves as a motivating factor to buy sooner rather than later, and not limiting the scope of the sale will draw in more people.

Incite a Second Purchase/Customer Retention

Most of the buyers you work so hard to acquire only buy from you once. These are known as one-time buyers, who do not provide an ROI that is substantial enough to grow your business.

In turn, a discount enticing a buyer into a second purchase can provide a substantial payoff – particularly since many statistics show that it is at least 5 times more difficult to acquire a new customer than it is to retain one.

Additionally, it is very important to keep a close eye on your margins and Customer Acquisition Cost (CAC) as you apply discount tactics and strategies.

Reactivate Fading Customers

Design your discount offers to solely reach inactive or fading customers, instead of your Most Valuable Buyers (MVBs). If your data indicates that someone hasn’t bought from you in a while, a timely, personalized discount offer could be the difference between winning them back and losing them forever.

Reward Loyal Customers

Send a special discount for your product or service to reward your MVBs for their loyalty and incentivize them to make further repeat purchases. Research has shown that discounts and coupons are the top-ranking tactic for driving loyalty with 61% of consumers saying they use them.

2. Segment Your Customer Base [Know Who to Discount to and When]

By segmenting your customers into groups, you can customize your discounts based on their respective buying tendencies and purchase history. 

Each of these can provide actionable information about your customers’ lifestyles, lifestages, incomes, interests, and the probability that they will buy from you again.

Equipped with a Predictive Marketing Automation (PMA) platform, you could send timely, personalized discount offers to the right person, at the right place, at the right time.

For example, if you sell furniture, kitchen appliances, roofing, or landscaping products, you have the ability to send discounts to people you know for a fact is a new/prospective homeowner – and is therefore much more likely to respond to the sale. 

Create Reference Tables

Reference tables are built from the various types of transaction codes used to track retail or online sales in POS systems. These typically include customer data, transaction data, and product data.

For example, if a buyer enters a furniture store and purchases a couch on clearance (where the price has been dramatically reduced), that particular item would have a special transaction code indicating the markdown in price.

This simple set of information can be used to form a clearer buyer profiles. For instance, if the person who bought the couch also purchased other items on sale (either that same day or over a longer period of time) he/she could be categorized as a discount buyer.

3. Test Multiple Discount Tactics and Campaigns

There are a wide range of types of discounts you can use, so be sure to pick the kind of discount that best fits your overall goal and your target customers.

Examples include:

Bundled

Instead of dropping the price of one product in particular, you can lower the price of specified group of items bought together.

This increases the number of items you sell, which means more revenue per order and less costs to package and ship each order if you work in e-commerce.

Seasonal/Special Event

Two common discount strategies revolve around holiday and seasonal sales. For instance, the automotive industry takes advantage of most holidays (i.e. President’s Day, Memorial Day, Labor Day) as catalysts to drive consumers into their showrooms.

Purchase Volume

In this case, buyers will pay less overall for a particular item if they buy a larger amount. This encourages them to purchase a greater number of units per order, while also spending more than they initially would have if they simply bought one of the items on its own.  

This is also an excellent tactic if you are looking to make room for more inventory or heighten the average profit of each order.

Free Shipping

Offering free shipping can be yet another way to persuade a customer to purchase and increase overall sales.

Since a downside of free shipping is increased packaging and delivery costs on your end, a solid way to cover your bases is by only offering free shipping when a customer spends a certain amount (like $35). 

This can actually entice buyers to spend more on your site on other items simply to cross the free shipping threshold.

Buy One, Get One Free

There are instances when a single discount on its own isn’t enough to draw in a sale. It’s no secret that most shoppers would prefer to receive an item that is “free” rather than at a discounted price.

An effective way to do this is by pairing a popular more expensive product along with a free one that is either less expensive or hasn’t sold as well.

Cross Sell/Upsell

Since discounts bring more people into your store (whether brick and mortar or virtual), they offer great opportunities to cross sell or upsell additional products in either the same or a similar category.

When certain items are on sale, tailor suggestions that would either complement or supplement each respective product. For some buyers, as long as they’re getting a deal on one item, they won’t mind paying full price for another related one.

Conclusion

There are a variety of effective methods to use discounts to your advantage. You can acquire new customers, generate more revenue from your existing customer base, enhance loyalty, and serve as the difference maker that sways buyers away from your competition.

Following and enacting the steps and tactics listed above will help maximize both the value and utility of your discount practices. This ensures that your discount campaigns will serve (rather than stifle) your business goals and increase the overall potential for further growth and success down the road.

What is Machine Learning?

Machine Learning (ML) is a subset of Artificial Intelligence (AI) geared to improve data analysis and model building via pattern recognition.

Through ML, computers can get better at identifying patterns over time and make their own informed decisions as they ingest more data.

Let’s examine ways machine learning is helping businesses improve their marketing efforts to drive sales, increase Return on Investment (ROI), and improve the customer shopping experience.

Predictive Analytics and Insights

For marketers, the end goal of ML is to send timely, personalized, relevant messages and product recommendations that truly resonate with consumers and incite them to make initial or repeat purchases.

Tools like a Predictive Marketing Automation Platform (PMA) utilize ML to apply algorithms and statistical models that target specific buyer segments. From there, they proactively analyze (and ultimately aim to predict) not just their behavior, but their intentions as well.

In the age of Big Data, this necessitates a degree of speed, aptitude, and accuracy that is simply beyond the scope of human capacity. Thanks to advances in ML, the whole process can be implemented autonomously in real-time more efficiently than ever before.

The Buyer Lifecycle

Precise targeting and forecasting requires an intricate understanding of where each customer in your base lands within the Buyer Lifecycle (BLC).

ML analyzes email behaviors, past purchases, web browsing/purchasing habits, and external data sources to calculate how engaged certain customers and prospects are at any given time and divide them into segments.

For example, if a customer has not bought from you in a while, an automatic message can be deployed in an attempt to persuade him/her to come back to your brand and buy again. This actively reduces churn rates and funnels more customers back into your active customer base.

On the other hand, there are customers that spend more money, more often than the rest. These are known as Most Valuable Buyers (MVBs). ML can acknowledge these spending patterns and send special “VIP only” messages both acknowledging and rewarding MVBs for their loyalty – an effective form of positive reinforcement.

Customer Acquisition

ML can also help you calculate a prospective customer’s potential future lifetime value (FLTV) and autonomously engage them through multiple acquisition channels.

ML capabilities can both determine customer value and autonomously respond through multiple acquisition channels. They also help you decide how much you can spend on acquisition to successfully meet your goals.

Improving the Customer Experience

These days, most consumers don’t just desire a personalized shopping experience – they actually expect it. Econsultancy recently referenced a consumer survey that found 64 percent of respondents now expect an individualized experience, while 85 percent consider an individualized experience to be important.

Rather than sift through immense piles of data to try to get to know your customers better and generate personalized relationships, ML can swiftly cater to a customer’s wants and needs almost instantaneously.

This can come in the form of chatbots that respond directly to customer queries for a more streamlined shopping experience, or recommendation engines that make suggestions and guide customers towards favorable products they’re more likely to buy based upon an automated analysis of past browsing/buying behavior.

Conclusion

This is the age of one-to-one marketing, where reaching buyers on a personal level via the proper channel is becoming more essential than ever.

According to a recent global survey by Google and the Massachusetts Institute of Technology Sloan Management Review (MIT SMR), 74 percent of respondents said they believe their organization’s current goals would be better achieved with greater investment in machine learning and automation.

The timeline to reach customers has changed dramatically. Given the way people shop today, you have to be able to respond to both their inquiries and behaviors almost instantaneously.

While ML will not magically do everything for you, it is certainly a driving force in the marketing industry that is helping retailers acquire, retain, and satisfy customers at a higher, more consistent rate than ever before.

The Guide to Marketing Nirvana [Step 7]

Since deciding to invest in your Predictive Marketing Automation [PMA] platform, you’ve generated a wide range of actionable customer intelligence and insights along the way.

You’ve integrated all relevant data and enhanced your database so you know more about your customer base than ever before. You also have a new, addressable marketing segmentation strategy that both targets and messages the right customers at the right place, at the right time.

You’ve learned the process, arranged your data, and implemented actionable programs in place, but what do you need to keep your eyes on to know if your organization is staying the course and truly headed in the right direction?

This final section will show you how to monitor and alter your campaign metrics over time to maximize your ROI and ensure sustained marketing success.

Revisiting Customer Lifetime Value and the Buyer Lifecycle

In order to achieve sustained success, you must keep a constant eye on the value of your customer portfolio.  Specifically, what will these customers be worth to you in the future? What is their expected Lifetime Value (LTV), particularly their Future LTV –  and how many of these customers are actively purchasing from us, revealed by the Buyer Lifecycle (BLC) statistics we have discussed previously. Keep in mind, these are just two metrics to keep track of  in addition to all of your other metrics of profitability.

You should always strive to increase the Future LTV of your customers. If their projected value is increasing as a whole, you’re making the right moves. On the other hand, if it’s decreasing, you want to analyze your PMA dashboard and understand the causes behind it.

When you log into your marketing system, you should have a customer intelligence dashboard with many metrics that allow you to understand the overall viability of the customers you have and see whether their value is trending upwards or downwards over certain time periods.

Below is an example of typical PMA customer metrics available through the BuyerGenomics™ dashboard:

By viewing all nine of these operational metrics over any specified timeframe, you can analyze how you’re performing from day-to-day and adjust accordingly.

Additionally, other metrics such as the last transaction date, to determine the recency of purchases, number of transactions, and the amount/frequency of individual customer purchases provide valuable insights. For customer profiles,  PMA’s will typically monitor a range of demographics and behaviors, including buyers by state, dollar amount of transactions by customer, and gender, as shown below:

When viewing your Buyer Lifecycle (BLC), keep an eye on the percentage of your database that is either fading or at risk to become dormant, and focus on shifting those buyers back into either Active or In Market.

In essence, the BLC helps you understand how well you’re inciting brand engagement in real time, and how many customers are actively shopping for your brand.  The chart below summarizes the Buyer Lifecycle Stages.

5 Key Strategies [And the Metrics that Guide Them]

From a database marketing perspective, there are many different strategies that companies deploy to increase profitability.  

This series has highlighted 5 Core Strategies that Marketers use successfully.  Let’s revisit them here:

1. Convert 1x Buyers

One-time buyers represent the largest overlooked opportunity for retail commerce marketers today. In fact, it has been that way as long as there have been retail sales.

Rather than focusing on the Trial (one-time purchase) population, organizations instead remain focused on acquisition as an avenue for growth.

Yet the grim reality is that the majority of those acquisitions lead to just a single purchase with no subsequent value.

Meanwhile, numerous published studies illustrate that the cost of acquiring a new customer is at least 5 times the cost of maintaining an existing customer. This results in a significant waste of time, money, and resources that could be focused on cultivating repeat customers.

2. Grow and retain Most Valuable Customers (MVBs)

The objective here is to treat your MVBs like the special customers that they are.

In turn, provide these customers with recognition, along with all of the special privileges they’d expect to have as a highly valuable and loyal customer. Special care should be given to monitoring this segment of your customer universe.

3. Acquire higher potential customers

Simply put, PMA intelligence guides you to fish where the big fish (high value customers) are.

We’ve talked about psycho-demographics and maintaining promotion history, and there are other special attributes you can use help find potential customers

All of this information can be used to inform media allocations and create acquisition models to improve customer acquisition efforts. Equipped with the right models, you can calibrate your acquisition efforts and maximize the return on acquisition efforts.

4. Grow high potential non-MVBs into MVBs

Some customers from the get go show signs of very high potential.

These are the ones that typically have higher spend in their first months as a customer. This presents an opportunity to quickly target them with special treatments in order to grow that potential as quickly as possible.

Rather than treat them like any customer, begin to treat them like the special customers you believe they can be.

Cater your messaging by providing them with different incentives that can trigger potential sales. Begin to treat them like you recognize they are a special customer.

5. Rescue fading and at-risk customers

These are the people who are fading and at risk of stopping purchasing from us altogether.

Since we understand through our buyer lifecycle stages that there is an expected repeat purchasing window for our universe, there’s a time to take action and reach out to customers before they become permanently dormant.

Time is always of the essence. The longer you wait, the less likely they’re going to purchase again and shift back to Active status in the BLC.

There are thousands of examples, but once the customer is rescued, a PMA allows can help you identify the timely, relevant actions and messages that actually brought that person back. From there, you can attempt to further cross sell and upsell based on whatever made them successful.

Either way, whatever offer or treatment brought them back, you want to be able to capitalize on that in the future.

Valuable Non-MVBs

Keep in mind that while MVBs are extremely important to cultivate, they generally only make up 15 to 20 percent of your customer base. Therefore, while the other 80+ percent may not be spending as much or buying as frequently, they remain a critical component of your business.

Do not underestimate the role of your “average” customers. They are still actively shopping from you, and even if they never become MVBs themselves, they still have the power to refer others to your business who may become heavy spenders themselves.

Campaigns

As retailers introduce new product lines – particularly as the seasons change – there are campaigns messaging to everybody in your customer base.

PMAs can help personalize these new product campaigns both effectively and intelligently – helping you to determine which messages are most effective for certain customers while managing all of your other business needs on a day-to-day basis.

For instance, if you are a clothing retailer, some of your customers may purchase from you throughout all four seasons, while others could only buy during the summer.

Therefore, smart campaigns treat each customer differently, tailoring communications to their seasonal purchase patterns and maximizing relevance according to the particular data you gather about them from your PMA.

Conclusion

The reality of today’s business environment is that marketing and technology have converged and they are continuously evolving and shifting. The emergence of the cloud is changing the game for everybody, and marketers have access to powers that they never had before.

That is precisely why you need a tool like a PMA to serve as the command and control center that guides your business and marketing endeavors. It lets you know if you’re creating better customer relationships, increasing customer value, which of your products are popular, and which are no longer attractive.

Basically, PMAs let you measure the health of your business from a range of perspectives, including:

• Customer
• Product marketing
• Inventory
• Financial

This helps you to understand every aspect of your business in real-time and try new strategies to become more successful.

The real distinguishing factor that a PMA offers as opposed to what many other retailers are doing today is that it fully integrates your data in real time. This offers a customer perspective that was once historically absent because client purchases weren’t addressable or identifiable.

In fact, you can achieve these marketing and technology benefits much faster than ever, and for a price that is a mere fraction of what it used to be, and much faster than ever. Nowadays, PMAs are achieving real-time updates and allow you to respond to business/customer needs at a rate that no one could have dreamed about years ago.

The capabilities of a Predictive Marketing Automation platform are no longer a luxury – they are a necessity to stay afloat in this competitive, always evolving retail landscape – much in the same way you need electricity to keep the lights on. In today’s digital age, customers have high expectations from retailers.  Meeting these expectations will require the application of data, artificial intelligence, machine learning, and database marketing strategies for the foreseeable future.

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The One-Time Buyer Problem

One-time buyers represent the largest overlooked opportunity for retail commerce marketers today. In fact, it has been that way as long as there have been retail sales.

Rather than focusing on the Trial (one-time purchase) population, organizations instead remain focused on acquisition as an avenue for growth.

Yet the grim reality is that the majority of those acquisitions lead to just a single purchase with no subsequent value.

Meanwhile, numerous published studies illustrate that the cost of acquiring a new customer is at least 5 times the cost of maintaining an existing customer. This results in a significant waste of time, money, and resources that could be focused on cultivating repeat customers.

Do you have a “one-time buyer problem?” The solution is within your reach by following this simple 5-step process.

Step One: Assemble Key Data for One-Time Buyers

First, we’ll share and discuss the “Simple Six” One-Time Buyer Data Points you can use to solve your one-time buyer problem. The good news is that most organizations either have them readily available, or can put them together with some help.

• Valid customer record & contact information
  You must have a deduplicated single record of the customer – with all transactions rolled up under them – in order to know who your one-time buyers are (and aren’t). You also need sufficient personally identifying information (PII) and a method of contacting them. This includes their full name and a combination of postal/delivery address, phone, cell phone, and email. These are required to both complete a valid/merged customer record and provide a means to contact them with a personalized series of communications that are unique to their current state/situation and behavioral profile.
  

• First Transaction Information, Buyer Source and Offer
  You will need to know when that first transaction took place, what was purchased, if a special offer was tendered, and the source of the customer. The number of items and the SKU’s in that critical first “trial order” are generally good predictors of the probability of a second transaction.
  

• Transaction Amount
  The amount the buyer spent on the first order says more than the profitability (or lack thereof) on the first sale. It’s also indicative in many cases with the probability that they will order again in the future.
  

• What The Buyer Purchased
  In addition to knowing how many items were in the order basket, we also need to know what they bought – including the Category and SKU of the item.

• Date and Time of Transaction
  These are really two separate data points we split out and use for different purposes to solve the problem, but are usually captured in a single “time-date stamp” on the transaction. It tells us how much time has transpired since the first transaction so we can compare this buyer to all other buyers and determine whether or not they are more likely to buy again. Going beyond just “recency,” we can gauge one or more purchase windows for the individuals with a higher probability of a second transaction – or determine if they are just a lost opportunity.
  

• The Profile of The Buyer
  Who is this buyer? Demographics and lifestyle intelligence give us an extra advantage in understanding who our one-time buyers are. Are they affluent or of limited means? Do they have children at home? Are they skewed towards Millennials, Generation X, or Boomers? Merely using a well-worn story about your customer is an assumption or shortcut that has proven detrimental in cracking the one-time buyer problem.
  
  “Our customer is young, rich and beautiful” may be a true statement, but what about the 1x buyers who are Boomers? Will you be relevant or tone deaf? The answer to this question helps determine whether or not you will move a trial buyer into loyalty and an evergreen stream of profitability.

These are very different customers, and our communications can be engineered in simple ways to spark them into a transaction and perform better when we speak in their voices and evidence our relevance to the customer. For example, personalizing an email’s subject line, hero shot, or the cellophane wrapper in a package can go a long way towards subsequent sales or more missed opportunities down the road.

Step Two: Rank Your One-Time Buyers by Aging

When we rank buyers by aging (a.k.a, recency), we’re determining how long it has been since they spent with us (note: this is not a ranking based on the age of the person). When we do this, we discover who has bought more recently and who hasn’t bought in a long time. This spectrum can be expressed as a distribution and in most databases, it’s not a normal distribution.

The Normal Distribution curve is a shortcut that most folks think about populations: it has a) total area under the curve +1 SD = 68.26%, +2SD’s = 95.44%.

However, your frequency of purchases almost certainly does not follow a “normal” distribution. It most likely either has a huge spike around 1 purchase, or is negatively skewed.

A real example of distribution by purchase shows that one-time buyers skew well below the often imagined “norm” or centerpoint in a normal distribution. This negative skewness illustrates that while it may seem “normal” that the typical customer buys a few times, we can clearly see in retail customer bases that most customers buy just one-time. This illustrates the need for addressing the problem proactively and early.

Notice also how the best spending customers that are the most loyal to the brand and have less time between their purchases, a requirement for a customer who spends a lot more. This is not to be confused with the fact that the majority of revenue is coming from the very large population of one-time buyers. Instead, it underscores the magnitude of the opportunity to sell again to your one-time buyers.

Step Three: Calculate the Window of Two-Time Buyer Purchases

Fortunately, we don’t have to solve the one-time buyer problem using only data about our one-time buyers. This is because all repeat buyers were once one-time buyers. Otherwise, it would be nearly impossible.

You almost certainly already have some two-time or more buyers. These individuals also have value in predicting when future purchases happen. The key is in the timing between the first and second purchase. Therefore, the goal is to understand both that behavior and its respective timing.

Step Four: Calculate The Inter-Order Purchase Time

We start identifying that window by looking at when historically our buyers made their second purchase. That’s measured as the difference between the date of the first purchase and the date of the second purchase in days. You’ll have to do this for every customer, next, compute the median number of days. We refer to this as the Golden Window for trial buyers.

Lastly, if we were to look at the distribution of the number of days between first and second purchase, we could determine if our repeat buyers might fall into different groups or clusters of behaviors that warrant further segmentation.

In the example below we have a distribution of customers by the days between purchase. In this particular example, there is a high probability opportunity to sell at about 114 days, and a second (even if its smaller) opportunity to sell at around twelve months.

The one year window is sometimes referred to as an anniversary purchase, and may coincide with a birthday or seasonal event (like travel for spring break). These cases in which more than one opportunity exist may indicate a dual universe with different types of customers, suggesting assignment to different communication groups to take full advantage of different buying behaviors.

Step Five: Campaign Execution

When we’re entering one of the spikes on the distribution, we see the probability to make the sale has increased based on the timing. This is an opportunity to sell, and we need to contact the customer and make a compelling offer. The conversion rate can be improved by leveraging the other data points we described in the “Simple Six” earlier, including the following:

1. The initial source and offer that led the customer to her first purchase offers key insights on those offers and discounts that will work in the future.
2. The Transaction Amount tells us if they are a high ticket buyer and if we should position more premium products. This also requires us to consider the number of items in the first cart. Many low cost items vs. a single high ticket item are indicators of different types of buyers. Your offer should distinguish between them.
   
3. Your buyer’s demographic and psychographic profile is also an opportunity to tailor your creative and messaging around him/her. If we know our one-time buyer is a Millennial, Generation Z, or a “Global,” we’ll need to communicate differently than if they are a Boomer.
   
   Tailoring subject line, creative, message, and offer/call-to-action in either an email or the cover of a catalog or postcard has been shown to increase both response and revenue per campaign.

Some Customers Are Already “Lost”

There is a portion of your one-time buyers that stopped buying from your brand (or at least from you) long ago relative to those who bought a second time. These individuals have the lowest probability of buying again, yet should be the target of “reactivation campaigns.”

By personalizing a reactivation offer based on what we know of this one-time buyer, it increases the likelihood of obtaining a second purchase.  If the data shows that the customer has a high potential value, we would be foolish not to try and engage them. Systematic testing of reactivation offers by segments provides retailers with the best opportunity to increase purchases from one-time buyers.

Conclusion

By definition, one-time buyers are retailer’s largest customer retention opportunity. Increasing customer retention rates is one of the most significant opportunities that retailers have to improve profitability, according to many published studies. Thus, the one-time buyer problem is one worth solving.

While most retailers offer a welcome series of communications, the opportunity exists for many retailers to improve upon such series by applying the simple data elements and promotion timing insights mentioned in this article.

For more information on how you can address your one-time buyer opportunity, download our full whitepaper, “Solving the One-Time Buyer Problem” by filling out the submission form below.

The Guide to Marketing Nirvana [Step 6]

Customer Growth

Growing a business is actually very simple, as any new MBA will tell you. To grow, all you need to do is increase sales to existing customers, acquire new customers, or both.  

But the truth is, as new MBA’s quickly discover, growth is not easy and customer acquisition is very difficult – particularly in this day and age where marketing has suddenly become so complex. As consumers are evolving in the digital world, their access to (and demands for) information has changed – particularly in the way they shop.

Due to these shifts in consumer behavior, acquisition efforts – more so than ever before – must be implemented using a range of data and analytical tools across a variety of channels.

We’ve discussed managing current customers in the first 5 steps of this series.  In this post, we’ll take a close look at finding new customers.

Segments and Customer Personas

Since the beginning of this series, we’ve stated that targeted acquisition requires a keen understanding of your customer universe and the different segments that you are marketing to.  After all, customer segmentation is fundamental for both prospecting and managing current customer relationships.

In your acquisition efforts, you may find that different messages and offers are more effective for certain segments.  Continuous testing is how you pinpoint the key segments – or customer personas – that you should hone in on and spend more of your resources attempting to convert.

Marketing automation systems provide structure around this testing process, by maintaining a history of how your tests performed.  Promotion history is perhaps the most valuable data available to support the customer acquisition process.

Timely Communications

While we have covered the idea of delivering timely, personalized, relevant communications to your customer base before, proper implementation of this tactic is even more important in the acquisition game.

The aim here is to look for indicators of intention. For example, if you are aware that a prospect is shopping for a new car and you see through location or other data that he/she has walked into a competitor’s showroom, that is a clear indicator that they are in-market (or looking to buy) and browsing elsewhere.

Or, if you become aware that a potential prospect is doing research on another competitive product online, make sure that you enter the mix with your own forms of communication as quickly as possible.

Going back to the notion of the customer journey, knowing that someone is in-market is valuable information. At that point, it’s time to take action, generate awareness, cultivate consideration on their end, and ultimately incite a decision to purchase.

Customer Acquisition Source

Frequently, the expected value of a customer can be very different according to the channel or media source that they came through and the offer that they responded to.

For instance, a customer found through a discounted offer on Facebook might have an average potential value, while a customer who discovered you through organic search could have a higher potential value – since they were actually looking for you in the first place.

Therefore, you can learn a great deal of valuable information about a customer’s value by knowing which source led them to your brand. Good marketing automation platforms capture this data.

Acquisition Allowables

An acquisition allowable (a.k.a, Allowable Acquisition Cost) is the amount of money you may spend in order to acquire a new customer, based on a customer’s lifetime value and the return on advertising spend (ROAS) goal. Every organization has a different method for calculating allowables, typically identified by both channel and offer.

Let’s say you calculate that a customer is going to be worth $100, and your return on marketing spend has to be at least 100 percent. In that case, you can spend up to $50 on each customer that you acquire. So if you spend $50 on an acquisition and need a 100% ROI, then each customer must generate $100 worth of revenue.

With acquisition campaigns, some efforts are going to be home runs, while others will be strikeouts. Marketing automation platforms allow you to keep close track of promotion history, revealing how effectively you are spending your money while acquiring new customers by channel and offer.

From there, you are in a position to refine the LTV of customers over time, refine your allowable advertising costs, minimize the strikeouts and optimize your media budgets.

Omnichannel Marketing

The timeline to reach customers has changed dramatically. Given the way people shop today, you have to be able to respond to both their inquiries and behaviors almost instantaneously.

Marketing automation tools allow you to both understand customer value and autonomously respond through multiple acquisition channels. It also helps you decide how much you can spend on acquisition to successfully meet your goals.

If you reach someone through multiple channels, there are likely synergies that exceed the sum of the parts (i.e. 1+1=3). In turn, the goal is to take advantage of all of the channels that are relevant to each customer in order to guide their conversion efforts.

Search and Social Media

If you’re using paid search through a search engine like Google to attract new customers, you can actually capture a detailed history of search terms and tie value to them. This is done by analyzing which particular terms brought in the types of customers who made larger or more frequent purchases and spending more to reach them due to a greater anticipated Return on Investment (ROI).

Without the ability to sort through your customer base and identify which ones are buying which products at certain levels of frequency, you have no way of assigning any degree of value to them. In turn, you cannot leverage social media channels as effectively as any of your competitors who possess that capability.

If you are selling women’s handbags and looking to advertise on social media, you can target your ads using LTV criteria from your customer profiles. By maintaining the history of such efforts, you may optimize your social media campaigns over time.

With its built-in database of customer intelligence and the ability to customize algorithms that calculate LTV, a Predictive Marketing Automation (PMA) Platform can quantify how much you should be spending on paid search, social media advertising, affiliate marketing, and email prospecting – as well as to whom.

Response Modeling

For many retailers, direct mail is very effective for customer acquisition efforts.  This is due in part to an analytical process referred to as response modeling.

The chief goal of acquisition response modeling is to rank-order prospects based on their relative likelihood to respond to a direct advertisement.

With this information in hand, you can increase response/conversion rates while lowering advertising costs, or optimize mailing quantities based on a given budget constraint.  Therefore, you can modify your marketing approach in a way that maximizes the financial parameters you are working with.

Lists, Compiled Databases, and Co-Ops

Prospect names for email and direct mail campaigns can be sourced from a variety of marketing service providers. Marketing service companies, including list owners, compilers, and cooperatives will offer retailers the ability to market to prospect names. Selection criteria may include list source, purchase history, demographics and other attributes.  Response models and other analytics may also be applied.

Having a key understanding of your current customer base allows you to better target prospect names from these third parties. Therefore,  a comprehensive history of promotion efforts will allow you to optimize these resources over time.

Location Advertising

Location-based advertising evolves your marketing capabilities in real-time by sending automated messages and offers based upon a customer’s smart phone’s GPS coordinates. A customer’s retail visitation behaviors, combined with their profile can be extremely useful information.

Marketing automation platforms are central to using location information. We expect to see the cost of location-based advertising continue to come down – increasing the ability of retailers to fully take advantage of this methodology.

General Advertising

Even in today’s landscape, not all marketing is digital and direct. General advertising campaigns include ads (like TV, radio, or billboards) where conversion attribution is harder to assess. Nevertheless, we can do a better job today than ever before in reading the results of these general advertising campaigns. Well structured tests and customer data platforms that quickly assimilate data help us provide timely results of campaigns.

Conclusion

In today’s digital environment, successful new customer acquisition requires an understanding of three key elements:

• Calculating customer value from different acquisition channels.

• Identifying which outreach efforts work (and which don’t) for different segments.

• Leveraging automated techniques to take full advantage of all potential opportunities.

Marketing pioneer John Wanamaker once said:

“Half of the money I spend on advertising is wasted. The trouble is, I don’t know which half.”

Thanks to PMA technology, today’s MBA’s will tell us that quote is no longer relevant. You now have the ability to know which half is working, and can spend the other half that you were previously wasting on channels and acquisition efforts that will prove effective in the future.

As we’ve stated before, these methods function as another component of closing the marketing loop and operating as a continuously learning organization. Ultimately, this is imperative if you truly desire to establish your brand in the marketplace and ensure a sustained competitive edge over your competition.

In our next post,  we’ll wrap up this series with a discussion of the key metrics to watch on your journey to Marketing Nirvana.

The Rise of AI [And What it Means for Retailers]

Artificial Intelligence (AI) is defined as human-generated computational devices and/or systems that are designed to exhibit “intelligent” abilities and behavior.

While this quickly evolving technology is already altering and disrupting a variety of industries, it has uncovered a wide range of new possibilities in the retail sector.

In fact, a report from CB Insights stated that from 2013 to 2018, AI retail startups raised a total of $1.8 billion over 374 deals.

The rise of AI and the ascent of e-commerce is affecting retailers in a wide variety of ways. Therefore, retailers must be cognizant of how rapidly this channel will engulf a bulk of their sales.

With the potential to create more jobs with brand-new skill sets, generate more personalized customer experiences, optimize inventory management, and streamline logistics and delivery, AI stands poised to lead the way in retail.

AI Usage by Format

The chart below clearly indicates that online retailers are ahead of the curve in adding AI capabilities. This makes sense given that the bulk of online retailers are fundamentally more data-driven companies than the rest.

Omnichannel retailers – who mostly started off as brick-and-mortar stores and later integrated digital functions and capabilities – are working to make up ground by developing a holistic, multi-channel strategy.

AI Usage by Subsector

The chart below shows how Apparel and Footwear – a popular category in e-commerce – is leading AI penetration among all single-category retailers. In  2017, online channels were responsible for 27.4% of total apparel sales.

Still at the top of the list is the multi-category sector, which includes the online mega-retailers like Amazon.

When asked about how much AI’s role in the company’s earnings, Tom Pinckney, VP of Applied Research at eBay, stated: “It is indeed north of $1 billion per quarter. AI and ML are driving incremental sales that wouldn’t otherwise have happened.”

Ways Retailers are Adopting AI

As a result of pressure from larger e-commerce giants and greater consumer demand, retailers from around the world are investing in AI to  increase operational efficiency and productivity.

According to a recent study by Capgemini Research, more than a quarter of the top 250 global retailers are incorporating AI into their organizations, and the global annual amount spent on AI by retailers is anticipated to eclipse $7.3 billion by 2022.

As a whole, retailers are substantially increasing AI development and deployment. Capgemini’s study found that 28% of the Top 250 retailers (and 41% of the Top 100) were implementing AI in 2018 – compared to 17% in 2017 and just 4% in 2016.

This is a clear indication that retailers are committed to investing in ways they can use AI to their benefit.

Chatbots

Chatbots are the most common AI applications in retail today, and \ allow businesses to accommodate their customers with 24-hour customer service.

Luxury retailer Louis Vuitton has incorporated chatbots into Facebook messenger in order to create a more personalized, conversational, and efficient shopping experience for their customers.

Equipped with Natural Language Processing (NLP), offer suggestions by asking pointed questions. This helps display the brand’s full product line while offering suggestions on particular items.

“We see messaging platforms as future key drivers of conversations with our clients, and potential for the integration of artificial intelligence and chatbot technologies to further enhance service to clients across these new channels,” said Michael Burke, Louis Vuitton CEO.

mode.ai – which has also teamed up with Levi’s to implement AI, visual search, and machine learning technology – helped Louis Vuitton develop the technology.

“We are still in the very early stages of AI technology adoption in the retail industry,” said mode.ai CEO Eitan Sharon. “The dominance of e-commerce isn’t just a trend, but an ever-growing arena, giving luxury brands like Louis Vuitton the opportunity to reach and sell to their customers in new and exciting ways.

“As shoppers continue to move online, the most forward-thinking companies will turn to AI chatbot technology to meet these shifting client demands,” added Sharon.

Robotics

Humanoid robots help customers by giving instructions and answering relevant questions, therefore enhancing foot traffic within the store.

By placing robots and touch panels, stores can help customers locate an item, get answers to their queries and find out how a product can make their life easier.

Walmart’s Robotics Research and Development

While the ROI of retail and delivery robots are still uncertain, Walmart’s patents displayprogressive plans, from voice-controlled unmanned aerial vehicles (UAVs) to synchronized drone delivery.

Walmart applied for at least 37 patents related to drones and ground robots since January 2017, compared to just 8 in 2016.

The chart below shows Walmart’s patent applications in comparison to Amazon – which is widely known for its ardent robotics patent development:

This data suggests that Walmart could be prepping for a disruption in the logistics field – particularly in the last mile – which is a major area of focus for their chief rival.

Additionally, customers in over 50 of Walmart’s stores will find more than just introductory robots. As part of an ongoing experimental exercise, they will also encounter robots with the ability to scan shelves for inventory assessment and modeling.

Virtual Mirrors

The new wave of fashion is closely linked to both personalization and predictive analytics/modeling. Equipped with loads of actionable data, algorithms will be used to predict (or even initiate) new trends and styles.

Last March, L’Oréal made waves by purchasing the augmented reality startup Modiface, which helped the company launch its “Style My Hair” mobile app that allows consumers to virtually “try on” various hairstyles.

Later that August, they teamed with Facebook to give customers the ability to project their styles on the network itself before clicking into the website and actually buying the product.

Competitive brands like Sephora and Estée Lauder also use AR apps that allow customers try on different virtual make-up looks. Retailers can then analyze the data collected on face shape, wrinkles, and skin tone to better predict inventory needs.

These virtual features help both fashion and beauty retailers in two distinct ways – they offer cutting edge ways for consumers to interact with their brand while simultaneously ingesting data on their tastes and inclinations.

Evolving Customer Preferences and Expectations

It’s undeniable that retailers across the board are fundamentally feeling the disruptive effects induced by the rise of e-commerce giants like Amazon on a visceral level. In order to remain afloat and competitive, retailers are under immense pressure to retool both their physical store and e-commerce strategies.

The scope of Amazon’s recommendation engine includes analysis of users’ past purchases, items currently in their cart, and past products they have rated in order to determine the most relevant items to serve shoppers. Reports indicate that Amazon drives approximately 35% of its sales through its product recommendations engine.

Technology Setting New Consumer Standards

The following statistics are from Salesforce’s latest State of the Connected Customer report

• 14% of customers said AI has already transformed their expectations of companies.
• 37% mentioned AI is already transforming their expectations and 36% said it will transform them within 5 years.

Therefore, over the next 5 years, 87% of customers expect more business growth through AI.

In addition, the survey found that a majority of customers have not only grown accustomed to – but are actually are fond of – AI-induced experiences.

For example, 56% of customers either like or love receiving personalized recommendations. On top of increasing site dwell time, these also help improve customer retention.

As technology evolves at such a frantic pace and AI continues to seep into consumers’ daily lives, they are becoming more comfortable and intrigued by the concept.

As a result, the study, determined that customers are 9.7% more likely to view AI as revolutionary instead of significant.

The main takeaway for retailers is the importance of understanding consumer tendencies/inclinations and properly implementing personalized content recommendations to improve consumer experiences.

Personalized Customer Experiences

As more and more businesses adapt to AI and its increasing scope of capabilities, the bar continues to heighten.

Customers have come to expect increasingly modern and seamless shopping experiences. As more people become used to shopping online rather than venturing to a physical store, they now anticipate similar levels of personalization – albeit via an automated, digitized source.

Retailers possess a tremendous amount of data on customers’ shopping experiences – both in-store and offline. If this data is cleaned up and organized properly, they can feed machine learning algorithms with user preferences and purchase history to suggest products and lead customers to websites or storefronts.

Equipped with the right tools, AI, predictive analytics, and marketing automation can be used to fuel the administration of customized products and deliver targeted, relevant product recommendations to the right person, at the right place, at the right time. This is something that Amazon does considerably well, and smaller retailers should follow suit.

After all, this is what consumers have come to expect. The coming years will bring about further advancements in the ways retailers approach and interact with customers.

Conclusion [The Future of AI in Retail]

The retail industry is at a critical inflection point. The biggest brick and mortar stores are facing significant external pressures, and today’s customers have come to expect a seamless omnichannel shopping experience, every time.

Retail is an industry that is consistently drowning in oceans customer data and in dire need of actionable ways to utilize it. AI has opened a world of possibilities for physical retail, and is revolutionizing the industry by making it affordable to offer a holistically personalized and engaging customer experience on a wide scale.

The failure to initiate direct, personal customer relationships is not an option in this new landscape. Overall, the biggest advantage retailers can gain from AI is accurate, efficient analysis and proper utilization of all of the customer data at their disposal.

AI has – and will – continue to alter the retail industry. The next few years will see continued enhancements to both customer experience and operations. However, retailers aiming to fully take advantage of these technologies in order to keep pace with giants like Amazon and Walmart still have their work cut out for them.

While many preliminary formulations – like chatbots – have been widely incorporated, there is much room for more extensive and impactful uses. In order to maximize AI’s true utility in this field, retailers need to invest time and resources necessary to achieve a full understanding of where it is today and the potential it holds for the future.

The Guide to Marketing Nirvana [Step 5]

The world of marketing and advertising is changing at breakneck speed.

Programmatic advertising buys see changes in the cost of impressions from minute-to-minute. The cost of search terms rise and fall based on competitive bidding. Batch-and-blast emails are flooding inboxes.

In addition, competitive marketing dialogues with customers evolve dynamically as digital activities change the odds of customers purchasing from retailers.

So, how can a small marketing department keep pace with these factors and other dynamics that are changing the marketplace?

Predictive Marketing Automation

Today’s marketers find themselves in their own combative cyberwar with their competitors and simply need to automate as much of their activities as possible.

A key tool, then, is a Predictive Marketing Automation Platform (PMA).  

A PMA accomplishes three things:

• It utilizes machine intelligence to effectively predict who is going to buy what and when.

• It detects when an individual has gone “in-market” and has a higher likelihood to spend inside a calculated purchase window.

• Once it notices the change in that consumer’s buying potential, it takes action on its own by contacting them with the right offer, at the right time.

These machine intelligence capabilities grow smarter over time as we learn how each customer responds or does not respond to various marketing actions. In order to win with customers and reach Marketing Nirvana, a PMA is an essential capability.

Recap/What’s Next

So, let’s begin with a quick recap of the steps to Marketing Nirvana that we have discussed so far in our series of blog posts:

• Enter customer data into a PMA — begin to keep comprehensive promotion and buyer history data over time.

• Understand who the customer is.

• Create Customer journeys based on value and customer purchases.

• Design email/digital campaigns to maximize sales; create a plan to test and learn over time.

Our next step in this sequence is:

• Leverage the customer’s relationship autonomously based on buying, promotion and engagement history. Enhance the customer’s journey by understanding where they are in their purchasing lifecycle and tailoring planned touches accordingly.  

All customer relationships have a beginning and an end. Moreover, those relationships vary from person to person and segment to segment. Each customer has his/her own marketing genetic code℠.  

While we discussed the Buyer Lifecycle in Step 2, its importance makes it worthwhile to revisit here in a little more detail.

Understanding the Buyer Lifecycle

The term Buyer Lifecycle (BLC) refers to the natural evolution of a customer/retailer relationship. It depicts your customer’s relationship and brand engagement from the moment that they become a prospect, an  in-market buyer, and finally inactive.

Many customers apply recency, frequency and monetary value algorithms as a surrogate for BLC. Unfortunately, those algorithms are typically manually intensive and error prone.

Every customer has their own unique lifecycle throughout their relationship with your company. A paramount goal of your brand should be discover customer behaviors while also influencing and creating new ones.

With PMAs, these actions are swiftly automated via predictive analytics and machine intelligence. They analyze the discrete events and metrics that either drive or diminish both revenue opportunities and customer value.

The notion that any customer file or database is mostly static is a misconception. In reality, your customers’ BLC is a dynamic, ongoing process that changes every single day.

A PMA utilizes email behaviors, past purchases, web behaviors and external data sources to understand how engaged certain customers and prospects are at any given time.

This allows you to see exactly where your current/potential customers are by autonomously designating them into one of six distinct stages.

The Buyer Lifecycle

Example of a Buyer Lifecycle Analytics (BuyerGenomics).

PMAs freely shift each customer among the six different stages according to a range of established variables and key signals.

These signals can include answers to the following questions:

• How often have they visited your website? How long since the last time?
• What did they browse? How close did they come to making a purchase?
• What are their respective buying patterns? How frequently/infrequently have they bought?
• Are they opening/clicking your messages? Or ignoring them?
• Have they made a trip to one of your stores?

BLC In Action

Due to advances in cloud computing, it is finally feasible for all marketers to maximize BLC visibility so that swift action can be taken whenever crucial shifts between stages occur.

For instance, a customer who recently shifted into the “Fading” stage requires a form of marketing intervention. This can come in the form of special discounts, privileges, gifts, or other offers that may reactivate the customer.

Meanwhile, for customers who have been labeled “Inactive” for an extended period of time, it may not make sense to waste anymore of your marketing resources on them.

On the other end, once a “Prospect” shifts to “Active,” you have your best shot at convincing them that your product is the one they want to buy not just once, but repeatedly and consistently.  

Send a personalized message, and strike while the iron is hot.

Each sector of the BLC involves a different approach and strategy. Therefore, a proper grasp of its intricacies helps to understand each customer better and consistently target them with relevant information.

AutoPilot

Obviously, keeping track of customer attributes and segments is a complex task. A PMA’s AutoPilot feature helps to simplify that process and make it actionable.

AutoPilot automatically allocates messages to customers based on their journey and BLC stage. Specifically, AutoPilot identifies those customers who need to be treated differently in your marketing campaign and then automatically triggers changes to outgoing customer communications.

These changes to planned customer journeys can range from personalized offers to attention-grabbing subject lines – all customized based on the probability of success.

To activate these automated treatments, simply click on a PMA’s enable menu to automatically initiate segmentation.

Wrap-up: Your Buyer’s Lifecycle and Automation

Buyers are the lifeblood of your business, and as is often the case, the Pareto Principle rules: 80% of profit normally comes from just 20% of your customers.

Earlier in Part 3 , we cited another compelling marketing statistic: increasing customer retention by just 5% increases profitability by 25 to 95%.

The marketing imperative is clear: Having an automated strategy to tailor messages to customers based on their buyer lifecycle and relationship with your company is the best formula to maximize customer retention and sales over time.

In our next section, we will discuss how PMA’s can help you acquire more customers through targeted acquisition strategies.

In addition, we’ll explain how competitive marketing dialogues with customers evolve dynamically as digital activities continue to alter the odds of customer purchase rates from retailers.

About the Author:

The Amazon Effect

These days, there is no denying the power of Amazon. Given their enormous influence in the world of E-commerce (and beyond), they offer the opportunity to dramatically increase both your profits and customer base.

With 100 million dedicated Prime members worldwide and many studies confirming that over half of all product searches begin on Amazon.com, it makes sense why so many small and medium-sized businesses (SMBs) have utilized Amazon to expand their customer base.

In fact, there are many prominent brands who have directly attributed their success to Amazon. In 2017, more than 20,000 SMBs exceeded $1 million in sales through Amazon.

However, while this certainly sounds appealing, there are a variety of factors to consider before diving into a relationship with such a giant company that has gutted many well-known brick and mortar stores – rendering them casualties of the Amazon Effect.

While the rewards can be very high, they also come with a range of risks. While Amazon can help you sell much more than you could elsewhere, you have to do it their way.

Although Amazon has created an abundance of options and a high level of convenience for consumers, its rising dominion actually poses a number of obstacles and threats for sellers.

Let’s break them down one by one before offering a way to turn the tables and stack the deck in your favor if you do choose (or have already chosen) to sell with Amazon.

1. Amazon is a Buyer’s Market [Thinly Veiled as a Seller’s Market]

Although Amazon presents itself as having a plethora of potential customers that can seemingly generate a level of demand high enough to outstrip the supply any single retailer could possibly provide – the reality is not that simple.

A condition of the seller relationship with Amazon is affording them considerable power over your pricing, inventory, and brand identity.

Equipped with this power, Amazon systematically pits its sellers against each other. This practice is based upon a science that methodically measures and commoditizes every brand and product with mathematical certainty.

In doing so, Amazon dedicates itself to maintaining a marketplace with the largest selection at the lowest prices. Therefore, even if a customer purchased your product, he/she will be introduced to thousands of other sellers that compete with you both on pricing and product.

Amazon HQ2

Actually, Amazon operated in a very similar manner during the well-publicised quest for its second headquarters. In a sense, they treated potential host cities in the same way that they treat their own sellers by luring them into a bidding war.

After the announcement, cities all across the United States rolled out their respective red carpets – promising substantial tax breaks and subsidies despite any potential drawbacks associated with doing so.

New York City in particular planned to offer Amazon tax breaks of at least $1.525 billion and cash grants of $325 million, along with other incentives to have one of its HQ2 sites in Long Island City. New York wound up winning their bid, only to have it retracted by Amazon back in February in the wake of opposition from members of the New York State Senate.

After the bid was cancelled, New York Governor Andrew Cuomo basically begged Amazon to reconsider by reportedly calling Jeff Bezos personally. In addition, an open letter was placed in the New York Times pleading Bezos to change his mind, stating that Cuomo “would take personal responsibility for the project’s state approval.”

The message Amazon sent was clear: “We make the rules, and we will only work with you if it is in our best interest.”

Credit: Statista

2. Amazon Requires Additional Costs

Amazon has created a medium through which an incredible amount of commerce flows. As a result, they are in a huge position of power, and can make even more money by charging tolls for access along the way.

In what has been described as a “pay to play” model, Amazon charges multiple fees for third-party sellers – either on a per-item basis or as a cut of sales. The latter of which can be anywhere from 15-20% of the sale price in addition to listing fees. There are also extra fees for special promotions like Prime Day and Lightning Deals.

Meanwhile, if you decide to register with Fulfillment by Amazon (FBA) – in which Amazon warehouses and fulfills your products – you will usually pay both a listing fee and a fulfillment fee.

Selling through Amazon also often requires paying for both search rank and advertising – since sellers need to develop some sort of presence on the site to gain eyeballs.

Selling ad space on its site has become extremely lucrative for Amazon. In 2018 alone, they reported $10.1 billion for their “Other” category, which they say mainly consists of sales from ad services along with sales tied to their other “service offerings.” In fact, Amazon does not even release its distinct earnings from advertising alone.

Moreover, fighting for ad space can be extremely competitive, and there is no guarantee that consumers will see your ad in lieu of other higher performing products.

As margins get squeezed, only a small group are going to rise to the surface and make it to the top. Usually, only a few select sellers get all of the eyeballs, while everyone else scrambles for whatever they can get.

3. Amazon Owns Your Customers

When you first register to sell with Amazon, you have the option to choose the aforementioned Fulfillment By Amazon (FBA) or Fulfillment by Merchant (FBM). With the latter, you choose to ship your products to each customer through your own logistics and operational processes. Therefore, you have access to the postal addresses of your buyers (more on that later).

Either way, you are never, under any circumstances, allowed to attempt to lead them to your own site.

The reason for this is simple. They are Amazon’s customers – not yours.

Amazon makes this fact very clear in a section of their Business Solutions Agreement:

“Any attempt to circumvent the established Amazon sales process or to divert Amazon users to another website or sales process is prohibited. Specifically, any advertisements, marketing messages (special offers) or “calls to action” that lead, prompt, or encourage Amazon users to leave the Amazon website are prohibited. This might include the use of emails, hyperlinks, URLs, or web addresses within any seller-generated confirmation email messages or any product/listing description fields.”

If you break this rule, you run the risk of being banned from Amazon permanently. At the end of the day, Amazon wants to ensure that they remain loyal to them – not you.

4. You Can be Suspended or Banned at Any Time

If you do not meet Amazon’s customer service expectations or receive too many negative reviews, you can get suspended – or even possibly banned – without a moment’s notice as these processes become increasingly automated.

Furthermore, sellers who supply inventory to Amazon wholesale can abruptly discover that their product listings have been yanked simply because Amazon’s algorithm (which strongly dictates the relationship between almost all of their sellers) decided that they Can’t Realize a Profit (also known as CRAPping out).

5. Amazon Owns an Expanding Portfolio of Their own Competitive Brands

The truth is, Amazon can be a platform provider, partner, and a powerful competitor all at once.

After perfecting the model for selling other people’s goods, Amazon has doubled down by swaying consumers to purchase their own products.

By 2022, Amazon’s private label sales alone are projected to reach $25 billion. Currently, Amazons owns and operates 139 private label brands and 473 exclusive brands – selling a wide range of items across many categories, including clothing/shoes, electronics, food, furniture, healthcare and beauty, household goods, industrial, and pet/animal products.

While some of Amazon’s private label brands sport its name – like Amazon Essentials or AmazonBasics, there are many more “phantom” brands that don’t. As a result, there are numerous people buying goods directly from Amazon without even knowing it.

Make no mistake. If your brand hasn’t already been challenged by an Amazon brand, the odds are that it will be.

Let’s take a look at another excerpt from the Amazon Services Business Solutions Agreement:

“You grant us a royalty-free, non-exclusive, worldwide, perpetual, irrevocable right and license to use, reproduce, perform, display, distribute, adapt, modify, re-format, create derivative works of, and otherwise commercially or non-commercially exploit in any manner, any and all of Your Materials, and to sublicense the foregoing rights to our Affiliates and operators of Amazon Associated Properties.”

If a certain product or category is performing particularly well, Amazon can just start selling similar ones under a new competitive (yet inconspicuous) brand. And once they see which products are succeeding, they ramp up their production and increase their presence on the site via advertising.

In addition, you don’t just compete with Amazon’s private label brands – you compete with them for share of wallet. Their goal is clear – to obtain as much disposable income from both their customers and sellers as possible.

While Amazon states that third-party brands still make up the bulk of its sales, how much longer could that be the case given their increasingly aggressive private label brand expansions that pull sales away from their sellers? 

Turn the tables – Independently Build your Brand and Customer Base

Although you cannot email Amazon’s customers, there is no place in its long list of clauses and stipulations that restricts you from utilizing direct mail.

Instead of FBA, if you choose Fulfillment by Merchant (FBM), you will have access to your customer’s postal address – which is important to have in this case.

While direct mail is a more expensive alternative to email, calculated investments can ultimately pay greater dividends. If you are mailing someone who already bought your product through Amazon and offer incentives to visit your own website, you can divert eyes towards your own site and personal offerings.

Once that happens, you can now initiate a direct, personalized selling relationship with the customers – something that you could never have done otherwise.

Therefore, you can turn the tables by using Amazon to generate a large volume of buyers, and then convert a steady stream of those customers into your own personal customer base.

This strategy offers a tremendous opportunity to methodically grow revenue, profits, and loyalty without Amazon pulling the strings and taking all of the credit.

Conclusion

The point here is not that Amazon is a “bad” or “evil” company. In fact, what it has managed to accomplish since its inception in 1994 as a small online bookseller is nothing short of astounding.

However, while Amazon may not necessarily be “out to get you,” they are dead set on capturing all of the profits in all of the categories that have them for themselves. You are merely content – or a commodity. Therefore, Amazon ultimately stands to gain more from your relationship than you do.

So before you jump into a selling relationship with Amazon, carefully consider what the conditions (and potential ramifications) are. Know that you and your brand will not only obtain a lower profit margin from each sale, you will also have a giant wall separating you from your actual customers.

If you do elect to sell on Amazon (or already have), consider the direct selling method to take back some control of your customer base. When dealing with such a giant company that carries such a strict set of rules and regulations, take advantage of any outlet you can to bolster your own personal brand awareness and develop personalized customer relationships for yourself.

When you own the customer, you own the future of your business and your brand. Amazon knew this decades ago, and look where they are now.