Why Conversion Rate Isn’t The Whole Story: Using Customer Data To Predict Value And Optimize Media Spend

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There have been some tremendous advances in understanding the value of digital (and offline) marketing initiatives in recent years. And with everything from tracking pixels to sophisticated analytics and attribution platforms, many marketers have finally begun to use the ocean of available data to guide their marketing dollars.

For those doing this well, it means knowing just how much it costs to acquire a new lead or customer, sell a product or service, or get people to interact and engage in upper funnel activities. For those not doing this, in most industries at this point in history, it means playing catch-up just to stay competitive.

But while all of the latest tools and technologies are helping us to figure out how our different marketing channels are helping us achieve X, Y or Z and at what cost, many of them are missing a critical component to the equation: the customer or prospect.

While it’s great to acquire a new customer, it’s even better to acquire the right kind of customer.

We’ve been fortunate at Cardinal Path (my employer) to see and work with the collective data and analytics technology stacks of some leading organizations, and a common theme has been the missing bridge between a goldmine of customer data and all of this marketing performance data.

If you can connect those dots, there’s a whole new level of value just waiting to be unlocked.

Are All Leads And Prospects The Same?

If you think about it, most of the reports and tools you’re probably using on a regular basis are working under one critical assumption: that all “conversions” are the same.

To illustrate the concepts here, let’s say that we’ve got ourselves a coffee shop (watch out, Starbucks!), and our marketing strategy is focused on getting new leads that hopefully become long-term customers.

Now, let’s say we’ve built out our multi-channel marketing plan to go get new leads, and we’ve done a good job of tracking all of these channels.

We’ve implemented a holistic analytics plan that can help us tie each of these marketing initiatives to the business objective of lead generation, and at a very high level, we might end up spending quite a bit of time reviewing data like this:

Tracking marketing channels

Look familiar? Ideally, you have this kind of visibility into your marketing programs these days. With data like this, you can quickly compare how each of your marketing investments is performing, you can calculate ROI and understand the volume of new leads you’re getting, and of course, you can drill down into any one of these and perform this analysis at varying levels of granularity.

But there’s one column in this table that we’ve all been content to live with even though we all intuitively know is not right: lead value.

All Leads Are NOT The Same

The truth is that there are all kinds of coffee drinkers out there, and there are some who are worth far more than others to us as a business. Take, for example, the person who walks by our coffee shop every day and gets the same double-no-fat-soy-iced-mocha-infused-green-tea-latte-hold-the-whip five days a week. That could be a great customer — far more valuable than the customer who comes in once a month to redeem a coupon for 50 cents off a large drip coffee.

Or you might find that the most valuable customer out there is the one who’s coming in every hour of every day to fuel the work she’s doing in the building next door.

caffeine-crazed-worker-ss

The point is, whatever business you’re in, there’s probably a pretty wide array of customer lifetime values in your database, and it’s also pretty likely that you’ve done some work to figure out who your most (and least) valuable customers are.

By looking into all the data points captured in even a relatively simple customer relationship management (CRM) system, businesses can begin to understand the lifetime value of their customers based on the products they’re purchasing, the average selling prices (ASPs), average order values (AOVs), the frequency of their purchases, and even the likelihood that they’ve ceased to be a customer (or churned).

Of course, this concept is nothing new, and it makes perfect sense. All of these customers are different, and we know that they’re all worth different costs to acquire. And yet, take a look at the marketing performance reports you’re working with, and odds are good that every lead/conversion/desired action is being assigned the same average value.

Finding And Dissecting Your Best Customers

In the end, if you’re trying to figure out exactly what value each of your marketing investments is providing you, you’ll have to take into account this customer value. To do this, there are some tried-and-true techniques that have been around for a long, long time.

For example, a simple value tier exercise can be a great way to start. Take a customer database, sort it by total-revenue-by-customer, and divide it into five equal parts. Next, have a look at the revenue being generated by those customers in each quintile, or tier.

Customer value tier segmentation

What you’ll probably find is not surprising: A small percentage of customers is making up a very large percentage of your revenue. So this leads us to some very logical questions around who these different customers are.

What are the attributes of a Tier 1 customer? What kinds of behaviors do they exhibit?

Luckily, a lot of this information can be provided by the data you probably already have. Some analysis and modeling can help you understand if things like gender, age, education, ZIP code or any behavioral or other data you may have can be predictors of value.

And with this data as a foundation, you’ll be well on your way to understanding exactly what kinds of new customers you want to be attracting. You can even predict the lifetime value of new prospects before you invest in finding them and making them customers.

Where Are The Valuable Customers Coming From, And How Can I Find More?

Now that you’ve got a great understanding of exactly who your best customers are, the question becomes, “How do I go and get more of them?” And this is why that bridge between customer and marketing performance data becomes so important.

While your CRM will have all kinds of data about your customers, their behaviors and attributes, many organizations have yet to effectively integrate all the online and offline marketing touch points with the CRM record.

The truth is, every ad that’s served and clicked, every interaction on a website or a mobile app and every social interaction has the potential to become a rich part of that customer data set and can be used to predict the value of future prospects.

Let’s also consider your digital marketing programs and the metrics you tend to use that measure success or failure. I’ll bet one of them is conversion rate, or the percentage of people coming from a certain channel or campaign who take actions that go toward your achieving a marketing goal you’re tracking.

In our case at the coffee shop, let’s say that we’re tracking downloads of new customer coupons as this conversion event. Channel by channel, we can compare performance, just like in the table above. But the problem here is that we don’t know what kind of customers we’re converting.

Very often, when we add in the customer data and do this customer value-centric analysis, what we find is that the channels with the highest conversion rates are bringing in the least valuable conversions.

By considering the type of customer we’re attracting with each of our marketing initiatives, we can essentially add a third dimension to what is typically a two-dimensional analysis.

Conversion rates and customer value

In the visualization above, we can very quickly see not just how many leads we’re getting or how effective a channel is at providing those leads, but importantly, we can also finally understand the value of those leads. With this data, we can more effectively model the best way to allocate our media dollars across the mix of channels and campaigns we run.

Treating Each Customer As The Individual He Or She Is

Turn the corner into truly powerful business decisions by bridging the gap between your marketing performance data and your customer data. Assign precise values to your prospects and customers that will inform your media spend, help shape your strategy and guide you to your best-fit customers.

To this end, e-commerce trailblazer 1stdibs (disclosure: client) recently undertook a project to gain a holistic view of its business integrating marketing data, customer data, e-commerce data and others onto a single stack.

“We were finally able to define different visitor and customer groups by new attributes and compare them against each other. Ultimately, this lets us understand what problems different groups are having so we can fix them, or which types of visitors are likely to be the most valuable to the ecosystem,” Jung Lee, head of Analytics for 1stdibs, said in a case study.

“It means we can provide just the right message to just the right person at just the right time and really be effective with our marketing dollars,” Lee added.

Now that’s competitive advantage.


Opinions expressed in this article are those of the guest author and not necessarily Marketing Land. Staff authors are listed here.


About The Author

David Booth is a co-founder and Partner at Cardinal Path, where he helps organizations use data and digital intelligence to gain competitive advantage in their markets. He is an author, adjunct professor, and public speaker, and as a consultant David has worked across five continents helping audiences ranging from C-level executives to technical implementation teams with digital analytics, business intelligence and digital marketing.

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