Net New Customer Acquisition
Net new customer acquisition is absolutely essential for every business. Even with an ambitious 5% customer churn rate goal, you’re still losing customers. Bring that up to the average of 9-10%, and within a couple of years you no longer have a reliable customer base. And even if – miraculously – you have perfect customer retention, eliminating acquisition severely limits your business’s growth potential.
On top of that, customer acquisition is hard to do right – and it’s expensive whether you’re acquiring the right customers or not. Digital marketing costs are rising five times faster than inflation, Google CPCs spiked 117% in 2018 (for the fifth year in a row), and Facebook CPMs were up 77% in 2018.
In the face of these numbers, it’s hard to imagine how you can acquire new customers cheaper or more profitably each year.
However, the secret to acquisition success is deceptively simple: focus on lifetime ROI – not just on one-time cost per click.
This isn’t a new concept by any means, but it poses a particularly difficult problem: How do I acquire customers that spend like my best customers? Those that spend often and generously are a sure-fire way to maximize your ROI (and of course, the volume of new customers you acquire matters as well), but you must be able to amortize the cost of acquisition over their lifetime as a customer.
To make explicit what’s implicit – acquire customers that will continue to spend and grow with you. This constitutes the “right” customer.
Success Starts with the Metrics
Before you craft a single message or even plan your acquisition campaign, you must first determine your acquisition goal and craft your key performance indicators (KPIs). Since we want to maximize ROI while maintaining customer volume and total revenue, the three most important metrics are your:
- Total number of new customers.
- Cost to acquire a customer (CAC).
- Customer lifetime value (LTV).
Total Number of New Customers
The total number of new customers is intuitive – but it’s important that you have a system that can properly deduplicate buyers and identify when a customer is truly new. Just because a customer used a different email address in two different transactions doesn’t make them new again, so your system must be able to recognize this. Otherwise, the number of new customers will be far too high, and you won’t be able to understand your customers’ actual lifetime value.
Cost to Acquire a Customer (CAC)
CAC is straightforward to define:
The nuance here comes in when you define your total cost. This can include marketing costs, employee wages, marketing software costs, and even overhead. However, it’s sufficient to use the cost of marketing media spend, which consists of your spend on Paid Search, Social Advertising, Display Networks, Direct Mail, and other media.
Customer Lifetime Value (LTV)
Customer LTV can get a little trickier depending on your business needs and model. How long is your customer’s lifetime? At what point do you need to break even or have positive ROI? Do you define customer value as Net or Gross LTV?
The best LTV calculations will use models and machine learning to predict the future LTV of each member of your customer base. However, many retailers can start simply and define LTV using the following formula:
- V = total revenue in a 1 year period
- P = total number of purchases in a 1 year period
- C = total number of customers in a 1 year period
- L = average customer lifespan
With LTV and CAC in hand, we can now easily understand our average ROI:
Now that we can determine whether or not our acquisition efforts are successful, we can plan our acquisition campaign. This takes the form of three distinct stages:
- Understand your Current (and Prospective) Customers
- Define your Most Valuable Target
- Optimize your Campaign
Understand your Current (and Prospective) Customers and Decipher their DNA
This is arguably the most important step in the customer acquisition process: defining who is suitable for your brand. The most efficient way to see just who those people are is by looking at your existing customers.
In fact, this step is so critical that – if done haphazardly and without careful thought – you will poison your database with low-potential customers. A low-potential customer will either spend just once or spend little with your brand, be discount seekers, and ultimately have little (or worse, negative) ROI.
With major ad networks like Facebook and Google consistently raising their media prices every year, this can put you and your business in a position where you are constantly treading water – just barely getting by churning through one-and-done customers.
Meanwhile, by defining the right target, we can maximize both the LTV of acquired customers and the number of conversions per click. This increases overall ROI by minimizing the number of total clicks (and marketing spend) you need to reach your revenue and net new acquisition goals.
And the best part? As time passes, these customers will continue to spend with your brand – consistently raising your overall ROI.
Define and Acquire the Right Target
To define and acquire the right target, you must consider four main types of data:
- Transactional Data
- Behavioral Data
- Attitudinal Data
- Demographic Data
But it’s not enough to simply collect this data. You need a system to combine this data into a single-source database so that you can understand and act on this data for individual prospects or customers.
Furthermore, you must be able to profile and segment these groups using all four data types simultaneously. In turn, whichever tool you use to collect, house, and process this data must also be able to combine different data sources, deduplicate records on an individual level, and provide an easy segmentation and audience generation tool.
Before we actually create our segments, it’s best to first understand why each data type is important.
Transactional Data: Understand How They Spend
Transactional data is anything and everything related to how your current and past customers have spent with you. It includes how much they spent, when they spent, what items they bought, and where they bought it.
In order to understand who is valuable today, you’ll need to calculate your LTV (either by using machine learning or the shorthand method described above). Having access to transactional data from multiple brands offers additional insight into the true potential value of a prospect before you even try to acquire them (Co-ops are particularly good at this).
Transactional data is also incredibly important for determining the entry-level products for new customers through market basket analytics. Entry level products play a key role both in what you communicate to your prospects via email, and what you show in paid search and social ads.
Behavioral Data: Figure Out What They Crave
Typically, marketers have little insight into who a prospect is despite the fact that they’re often sitting on a gold mine of behavior, interaction, and engagement data. While some marketers might think: “I only send mail to my engaged list, and I look at my GA account every day” – that’s only the tip of the iceberg.
For starters, channel data tends to be anonymous (this is also the case with Google Analytics). Most tools don’t actually let you retarget specific prospects – unless you hand off some control of your brand to the ad network overlords. On the other hand, if email is the only direct-to-consumer channel you use, you’re doing your business a huge disservice in this omnichannel world.
Behavior and engagement data extends well beyond the scope of opens, clicks, and channel. You must also consider products and categories browsed, user dwell time on such products, and the frequency with which they return to them.
In short – behavioral data informs you what your prospects crave.
Attitudinal Data: How do they Feel (about your Brand)?
Attitudinal data constitutes how a customer or prospect feels about your brand, your prices, and your products.
The simplest and most intuitive attitudinal data you have access to is your average star rating. A five-star rating means your customers like you, while a 1-star rating means…well, they don’t. Therefore, it should come as no surprise that more stars means more sales. Other people’s opinions influence consumer behavior, which is precisely why businesses care so much about net promoter scores.
The only problem with average star ranking is that it’s not so easy to act on. Having a five-star rating is great – but then what? With a system that collects individual customer ratings, you’ll have the ability to compile promoter scores for each individual. This allows you to identify customers and prospects that will positively impact your business via ratings, social media, and recommendations.
Demographic Data: Know your Audience
Demographic data includes much of who the customer is – including their age, income, family status, place of residence, and current lifestage.
While demographics can influence the messaging strategy you take – like displaying an image of an older, refined couple in your hero shot when you message your well-to-do Baby Boomers – it’s also an incredibly powerful indicator of not just what your prospective customers want to buy, but whether or not they can buy it.
Income and net worth strongly correlate with a consumers means to buy a product. If they can’t afford to buy what you sell at your price point – even at a discount – you’ll never sell to them. At that point, you’re better off excluding them from your acquisition efforts altogether – they’ll only wind up hurting your ROI.
Similarly, lifestages are important in determining a person’s desire to buy with you. Rarely would someone without a baby on the way purchase a crib – but we can almost guarantee a pregnant couple will.
Get Your Best: Segmentation and Lookalikes
Armed with our consolidated data, it’s now time to move on to the “how” of acquisition. With the modern modeling techniques that exist today, there’s little reason not to utilize lookalikes.
Most modern ad networks worth their salt handle lookalike modeling and profiling for you. This includes the advertising powerhouses of Facebook and Google. That being said, even if these networks use lookalike modeling, you still need to tell them who you want to acquire. If you give them a set of low value names, then those networks will only find low-value acquisition targets.
In order to crack open these networks to your advantage, use your current customers’ transactional data, behavior data, demographic data, and attitudinal data to acquire new customers that look just like your best customers.
But how do you define your “best” customers?
The most straightforward answer is those who spend a lot, spend frequently, and engage and like your brand. However, to figure out the proper weighting for these, you’ll need to test multiple segments to see which one performs best compared to our acquisition metrics: total number of new customers, CAC, LTV, and ROI. And whenever you utilize models, you should always test multiple different targets – lookalike models are no exception.
To test into your best lookalike target, you must:
- Start with multiple potential acquisition cohorts. These can either be chosen by you or determined by an autonomous system.
- Record the test results. If you use an autonomous system, feed them back in.
- Adjust your lookalike target based on the success of the tests.
Ultimately, when you have an established target, you must regularly refresh the lookalike names with new customers to better hone your feedback system. This refresh is ideally automated by the same system that deduplicates and identifies truly new customers.
Below are a few “best” customer segments to kickstart your testing.
1. Best Behavior
Arguably the most intuitive of the examples here, the “Best Behavior” lookalike target is exactly what the name implies: those whose purchase behaviors indicate that they will interact and spend the best with your brand.
The Best Behavior segment uses the following criteria:
- The top 1.5 deciles by LTV
- Recently Purchased
- Actively Engaged
- Net Promoter
In this case, “Recently Purchased” depends upon your customers’ purchase cadence. From the LTV formula below, you can use to estimate the number of purchases in a year, and then divide the number of days in a year to get the average number of days between purchases, labeled as :
Customers that have recently purchased are those whose last transaction date is within the last days.
2. High-Indexing Lifestages
Many companies struggle with how to choose the best segmentation solution for their total market. Predictive Marketing Automation (PMA) platforms can access and consolidate different lifestages via third party data sources.
These provide extremely practical information about your customers’ lifestyles, life stages, incomes, interests, and – perhaps most importantly – the likelihood that they will purchase your products in the future.
People in different lifestages tend to spend differently with different brands. This means people in certain lifestages may be more valuable to your business, so you’ll want to choose the groups that index higher than your average customers by value.
We can define this cohort as:
- Top 3 Highest-Indexing Lifestages by LTV
- Recently Purchased
- Net Promoter
To figure out which lifestages are over-indexing, divide the average customer value of the members of your lifestage groups by your true average customer value. In general, those indexing above 1.05 will be valuable, and any indexing above 1.15 are your prime target.
Considering a customers’ last purchase date will add an important dimension of recency so that you don’t attempt to acquire a lifestage that is no longer relevant to your brand. Layering in attitudinal data via the net promoter status will ensure that those in the top indexing lifestages buy your product because they actually like it – not just because they have the means to.
3. Top Promoters
As mentioned before, more stars mean more sales. Therefore, we want to leverage this beyond publicly displaying a (hopefully) 5-star ranking. This can be done by acquiring people that look like our top promoters, which is defined as:
- The top 1.5 deciles by Promoter Score
- Actively Engaged
- Bought at least once
Layering in engagement data is critical. Net promoters are valuable because they feel good about your business and your product today. In turn, if they are not engaging, there may be a reason why.
In addition to lookalike acquisition, this is an excellent segment for more advanced acquisition techniques, such as setting up a referral program. Offering minor benefits to members of the Top Promoters group can net you many affordable referrals.
What Should You Pay
Before we move one step further, remember: Don’t be afraid to spend to get high-value customers. You might be breaking even or losing on the first transaction, but the first transaction does not equal the full value of the customer over the lifetime of your brand.
Remember, by utilizing our transactional, behavioral, attitudinal, and demographic data, we are stacking the deck in our favor to acquire customers that will grow in value over their lifetime.
Use your target ROI and LTV calculation to determine your maximum CAC:
This is the amount you can spend to acquire a new customer on ad networks and other media.
Build an Optimal Campaign
With that said, the media cost often only gets the potential new customers entry to your site or the store – it doesn’t guarantee that they will convert. However, once a potential customer has landed on your site, they’ll start leaving behind valuable data about their intent. We can act on this in real-time to increase the probability of conversion – but only if you have a system that actively collects this behavioral data.
Note that an anonymous site tracking system is insufficient. While it may allow you to collect data on an individual’s browsing behaviors, it does not let you directly deploy retargeting efforts on those individuals in real-time – which will cost you real dollars that you’ve already spent to drive these potential customers to your site in the first place.
With proper site tracking in place, we can now respond to a user’s site interactions to increase the probability of conversion. While we can use any of the listed campaigns, it’s best to create a layered campaign that makes use of all of those listed below.
A good system will allow you to manage how these interact with each other, while a great system will manage them for you.
- Prospect Activation Series
- Many retailers implement a drip campaign when a user signs up to receive their newsletter. This is table stakes for any business, and should absolutely go beyond one simple autoresponder.
- Abandoned Cart Rescue
- When a user shows high purchase intent by adding items to their cart but fails to check out, it’s important to deploy a series of reminders for them to do so.
- Window Shopping Conversion Emails
- Users may also show intent in the products they browse or the categories they search. Retarget them using this information by sending messages that incorporate the products with the greatest dwell time.
- Exit Intercept
- There are key behaviors a user will demonstrate before they navigate away from your page – the two biggest indicators being inactivity (no movement on page for at least 30 seconds) or a rapid scroll back to the top of the page.
- When these behaviors are detected, intercept their exit intent with an on-page pop up. Call their attention back to the page, and present either an email signup form (so we can contact them later) or a perceived offer (to shift their interest back to buying).
With each of these tactics in place and properly managed, you will significantly increase the probability that the user will become a new customer (and that the money spent to drive them to your page was not wasted).
Customer acquisition is a critical component for the success of any company. But if done incorrectly, you’ll wind up acquiring low-value, one-and-done customers despite paying the steep cost for acquisition on ad networks. Without acquiring the right customers, your odds of retention and growing your ROI is slim at best.
In this whitepaper we have outlined what you need to know to run a successful acquisition campaign – from what data you need to collect, to who you should target, to how you can convert those prospects into valuable new customers and ensure a high ROI.