Transforming Your Data into a Marketing Plan
At this stage along the path to Marketing Nirvana, all of your POS and transactional data have been consolidated and filtered through PMA software.
This means that all of your retail information has been stitched together across all available channels – generating the template for the omnichannel, 360-degree customer view that the mega-retailers use today.
By using this comprehensive view of the customer, marketers can build their marketing plans with greater insights to address media spend, price promotions, special campaigns, and specific strategies for segments of their customer and prospect universes.
Insights include answers to the following questions:
- Who are my customers?
- Where can I find them?
- What message do I deliver?
- Which channel(s) should I use?
Who Are Your Customers?
The first plan of action is to enhance your customer transaction information with information that can help you build a marketing plan. List brokers, data brokers, and major compilers each offer hundreds of different customer attributes (or variables) for marketers to choose from.
Three critical types of actionable intelligence are available (from different sources, offering differing degrees of customer coverage):
- Geographic/Demographic – income, age, region, dwelling location/type.
- Psychographic – lifestyles, interests, hobbies.
- Behavioral – actual buying behavior/purchasing tendencies.
These different types of data offer marketers the essential raw materials to build a rich understanding of who their customers are and how best to communicate with them. There are thousands of permutations that can potentially be of value.
As you would expect, all of these variables have a cost associated with them. The data is not free.
Therefore, understanding how to use all of this information both wisely and cost-effectively can quickly become overwhelming – especially with such a vast range of personalized variables for sale throughout the marketplace.
But if you’re following these steps, there is no need to worry. PMAs takes care of the hard work for you by finding segments of customers that behave similarly and profiling them for you.
In other words, PMAs automatically find groups (or clusters) of customers that help divide your total market into segments that behave in similar ways with respect to your product offering.
A logical question at this point is, how do PMAs help you arrive at the best segmentation solution for your total market? A common technique deployed is a statistical method called cluster analysis.
Cluster analysis creates groups of customers based on maximizing homogeneity within groups and heterogeneity between groups of customers.
Each of these groups (or segments) can provide extremely practical information about your customers’ lifestyles, lifestages, incomes, interests, and – perhaps most importantly – the likelihood that they will purchase your products in the future.
There are many marketers who are not familiar with 3rd party data solutions. Even those who have some rough familiarity have likely used them less than they would have liked because of their high historical costs. However, in today’s world of “big data,” those costs have gone down significantly.
With all of this precious information out there, retailers need to seriously consider how to take advantage it.
Theoretically, you could peruse through all of the data available on the planet and create a custom cluster analysis that points to which variables most closely match your ideal customer base.
However, while some very large companies pursue this path, such a method is time consuming, expensive, and (worst of all) potentially wasteful if you wind up making poor decisions along the way.
Through its efficient utilization of third party data resources, a PMA makes your data smarter via perceptive insights and practical profiles through the distillation of demographic and psychographic database attributes.
By already pre-clustering all of the consumers in the US specifically for you and your business, you have a running start on better understanding your customer universe without the high costs of distilling a custom solution.
Instead, you can spring into action right away. And, you can always add new data to your database later if it makes sense to do so.
Powerful marketing opportunities arise when a member of your target audience transfers (or migrates) from one lifestage to another.
Your odds of customer acquisition dramatically increase when equipped with a repository (PMA) that can keep track of these shifts, respond to triggers, and autonomously deliver timely, personalized offers.
An example of lifestage migration is when an individual or couple moves from a rental apartment to a single-family home for the first time.
According to a NAHB study, buyers of new homes outspend non-movers by 2.6 times on such items as appliances, furniture, and remodeling.
Wouldn’t it be great to be able to send a timely, personalized discount offer for new furniture, kitchen appliances, roofing, landscaping products, etc. to someone you know for a fact is a new/prospective homeowner?
Well, it turns out that you can.
That ability alone gives you a significant competitive edge over the rest of the competition.
Actionable Segmentation and 1-to-1 Marketing
As with any marketing segmentation solution, the goal is to create a set of actionable segments that are both well understood by your organization and stable over time.
These segments typically consist of a set of available buyer information (including external data and product information) that allows you to better engage customers, automate the right messages to send, further understand the buyer lifecycle, and create new customer journeys.
For example, there can be multiple categories of clearly distinct populations that shop at a particular retailer.
If you want to get the most out of each group, you must market to each separately with deliberately distinct, exclusive messages.
When initiating any form of customer communication, your message should be as relevant as possible. This ensures firm engagement and an increased likelihood to respond.
In the retail example, a younger demographic might be much more receptive to sales on the latest fashions, while an older demographic might be more inclined to lean toward more traditional, conservative brand offerings. In turn, target your messaging to those who are most likely to be receptive.
Thorough cluster and lifestage development allows marketers to identify the natural pockets of opportunity for each customer without overwhelming them with unnecessary noise.
Blindly blasting universal messages to all sectors of your base will skyrocket the amount of irrelevant messages delivered. At best, those messages will be ignored. At worst, it could turn customers off from your brand altogether.
While developing multiple segments for a retailer, the approach should always be as pragmatic as possible.
Start by asking yourself a few questions:
- How many segments can your organization support?
- How many segments will allow you to maximize marketing effectiveness?
The answers can get tricky, because when a retailer deals with multiple segments, they should work to tailor their approach differently for each one. While there isn’t one set of answers that works for everyone, the considerations are the same for all companies.
Let’s say you sell food products. One segment of your base is vegetarian, one is gluten free, the second is both, and the third is neither. Each group should receive very different sets of promotions and recommendations.
This costs time, money, and resources to develop.
When you begin to grow and expand the number of segments you are marketing to, you also increase the amount of work necessary to cater to each one. This can get overwhelming fast, particularly for smaller retailers.
This leads to a key challenge – figuring how many segments are necessary to maximize effectiveness, while weighing that against the internal cost of maintaining the amount of segments and messages.
A PMA helps solve that quandary by providing swift personalization for each identifiable segment.
Regarding email messages, PMAs can deploy personalized, one-to-one blocks of relevant communication autonomously. This allows smaller retailers to be more productive in their marketing efforts across multiple segments with less overhead and greater traction.
Again, the heavy lifting is already done for you.
Where Do Your Customers Come From? How Do They Purchase Your Products?
Many small and medium sized businesses lack the capacity to track the range of factors leading up to the first point of contact with each customer.
This is a shame, because knowing where and how a customer relationship started may actually be more important than knowing the point of purchase itself.
With a PMA, you can capture valuable customer acquisition information, connect all of the dots together across channels, and build a strong data foundation going forward.
Acquisition Channel Analysis
The acquisition source – or the method/channel through which a customer relationship was initially formed – is highly predictive of how customer behavior will evolve down the road.
Say a buyer first came into contact with your company through your website. Perhaps they arrived at your site in the first place by clicking on a social media ad. From there, he/she subscribed to your email list and purchased a product on their iPhone with a discount code.
Meanwhile, another buyer actually walked into one of your retail stores and used a physical coupon from a mail-order catalog.
Wouldn’t you develop your discourse with the two differently? Certainly.
If you have a group of customers who are online-only shoppers, stick to the digital realm. If others are frequent in-store shoppers, focus on that realm, but still always leave the option to purchase online as well.
By understanding which communication channels are most important to each customer in your base, you can develop the right respective combination of media to reach them through.
This practice helps to determine where to invest your time and money, reduce wasted efforts, maintain relevance, and optimize Customer Acquisition Cost (CAC).
From there, you can lead them further along the right path on the customer journey by establishing the best messages to entice subsequent purchases.
This type of predictive element is extremely valuable. After all, the ability to accurately forecast what buyers are going to do next is something that all marketers strive for.
What Products Do They Purchase?
Obviously, you can glean a great deal of customer knowledge by tracking what types and categories of products they buy. From there, the objective is to maximize their lifetime value through new purchases and services down the road.
Market Basket Analysis
Market Basket Analysis is a form of statistical analysis used to determine which products customers normally purchase together.
For example, someone who purchases a surfboard is likely to buy another related item/accessory in conjunction – such as a wetsuit.
By understanding how products are purchased together, marketers can guide the dialog with customers in a way that is both helpful to the consumer and profitable to the company.
Another example could be after someone who purchases a particular brand of electric guitar, carefully tailored suggestions would arise suggesting typical pairings with certain amplifiers or effects pedals.
Meanwhile, a poor example of this method would be if a customer who just bought a lawnmower received subsequent suggestions about other lawnmowers instead of other supplementary products like hedge trimmers or leaf blowers.
Mistakes in the form of duplicate or irrelevant pairing suggestions dramatically decreases your chance of adding items into your customer’s cart, and can even damage your reputation in the buyer’s eyes.
Top retailers who successfully implement this practice consistently – such as Amazon – are able to maximize both quantity and price of each purchase through this practice.
This is because they had the resources to develop high-end software capabilities necessary to do so. Without a similar toolset (like those found in a PMA), how could others expect to do the same?
Cross Category/Single Category
How broad or narrow are your buyers’ interests?
If you sell winter sporting gear, an example of a single category buyer would be an individual who only purchases skiing equipment.
Meanwhile, a cross-category buyer would be someone who buys both skiing and snowboard equipment.
For instance, if you know a buyer is only interested in skiing, you would know to not waste your time suggesting anything beyond that category – even if it is technically something similar like snowboarding.
Accurately differentiating between various cross and single-category buyers serves to further personalize the offers you send to them. Is someone a hiker, fisher, and a camper? Or just one of those?
This is just another example of a simple, yet powerful concept and practice that are often overlooked by retailers.
What Are Their Needs [And How Can We Meet Them]?
Ultimately, marketing is about people, not products. Therefore, it is extremely important for retailers to understand the customers’ requirements for their goods and services.
How do customers want to be viewed and treated by the brands they purchase from? And, how does your product meet their needs better than the alternatives in the marketplace?
Simply speaking the customer’s language and catering to their needs accordingly holds a great amount of weight.
For instance, there are certain people who need to feel like their products are trending. Those who want the latest and greatest often desire feelings of prestige and recognition from both their sellers and their peers.
Some also wish to be viewed as insiders with access to exclusive offers, products, and treatment that others do not receive.
Meanwhile, there are others who always want to feel like they are getting the best deal possible. Focus on providing them with information on your latest sales and discounts.
With the proper tools necessary to conduct proactive data and survey analyses, you can easily understand the needs profile of each particular customer segment and design your mode of communication with each cohort differently.
Understanding the Buyer Lifecycle
The term Buyer Lifecycle (BLC) refers to the natural progression of a customer/retailer relationship. It depicts your customer’s relationship and brand engagement from the moment that they become a prospect all the way up until their final purchase.
Every customer has their own unique lifecycle throughout their relationship with your company. A paramount goal of your brand should be to work to both discover customer behaviors while also influencing and creating new ones.
With PMAs, such actions are swiftly automated via predictive analytics and machine intelligence. They analyze the discrete events and metrics that either drive or diminish both revenue opportunity 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.
|1. Prospects||Not yet customers.|
|2. Actives||Individuals currently engaged and/or spending with you.|
|3. In Market||Buyer currently shopping for your products and are prepared/likely to buy again|
|4. Faders||Subjects no longer purchasing at the rate their customer profile suggests they can.|
|5. At Risk||Buyers most likely to stop spending with your brand and fall into attrition.|
|6. Inactives||Customers who have ceased purchasing your products.|
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).
PMA’s freely shift each customer among the six different stages according to a range of established variables and key signals:
- 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?
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 repeatedly.
Send them a personalized message, and strike while the iron is hot.
Each sector of the BLC involves a different approach and strategy, and a proper grasp of its intricacies help to better understand each customer and consistently target them with relevant information.
It is always the marketer’s goal to understand the triggers that are likely to create sales in order to build successful campaigns.
The best way to do this is to know who your customers are, where they come from, what their interests/inclinations are, which channels they frequent, the types of products they buy, and how they want to be treated.
A PMA platform stacks the deck in your favor by giving you a cost-effective repository of marketing information that supports smart, sophisticated segmentation right from the moment your rudimentary transactional/POS data is uploaded (see Step 1).
Therefore, not only can you possess an advanced, expansive database that captures and categorizes comprehensive customer information in real-time, you also have access to vast amounts of previously inaccessible discrete demographic, psychographic, and behavioral information.
All of these factors combine to formulate the core components of each individual customer’s genetic code – or Customer Genome℠.
Now that you’ve put in the effort to know who your customers are, you have the ability to apply that information towards building intelligent, targeted, personalized, cost-effective marketing plans and strategies.
This leads us to the third phase of our series – learning how to dig deeper and narrow the scope even further to Create Customer Journeys and Segmentation Strategies.
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