Every day we hear the phrase “data is king” and for good reason: it is. It’s why most brands the world over have undertaken some kind of digital transformation initiative and invested in data lakes and business intelligence. Others have poured resources into data management platforms, customer management platforms, and have built teams of data scientists and data engineers.

But here’s the thing: very few are operationalizing all that data they collect. So while no one doubts that data is King it seems we’ve forgotten about the Queen -- you know, the one who takes what’s been brought into the house and ensures it’s put to good use. 

As an eCommerce leader, I speak regularly with my peers in the space, and too few of them say they’ve used their customer data to think beyond their initial personas or basic digital marketing audience creation. Even fewer have leveraged it to develop a cohesive strategy that’s deployed across the entire organization. That’s a missed opportunity, especially when one considers the many ways that data can enhance the way brands engage with their customers throughout the customer lifecycle. 

Personas Are Just the Starting Point

When most marketers think about building an audience and marketing to new consumers, they start with personas. Let’s say you’re a shoe brand, you’ll look at your best customers -- say people who buy more than ten pairs of shoes each year --  and examine their attributes. In this case, let’s assume they’re urban professional women, aged 25 to 45 who live in high-income households. So there’s your basic persona, and that’s who you’ll target, right?

Next, you’ll turn over those personas to marketing, whose job is to find the best places to reach those audiences. They’ll look for sites and channels that attract women like those you want to reach. And they’ll buy various location, gender and income-based datasets to home in on the exact audience. But guess what? While the majority of your best customers meet the criteria identified in your persona, you can’t assume that the majority of women in America who meet your persona criteria are willing to buy your shoes, much less at that same rate. This approach isn’t that much better than the classic spray-and-pray advertising. 

Here’s why:

First, two women living side by side, both moms, both living in high-income households, both in their late thirties can meet your targeting criteria to a tee but may have vastly different buying habits. One may be a shoe enthusiast, while the other views them as rather utilitarian, something she needs only because she can’t go through life barefoot. Targeting her would be a waste of your media budget.

Second, third-data party datasets are just an approximation anyway. We’ve all read stories by men who say the Internet thinks they’re women. Besides, GDPR and the California Consumer Protection Act are clamping down on a lot of third-party data, so ultimately you’ll need a new approach.

Personas are useful, but they are a very simple starting point. Demographics alone will not tell you whether a consumer is likely to buy your product. Behavior is a much better indicator of purchase, so why not target based on it?

Not All Consumers are Created Equal

Let’s say you embark on a persona-based, multi-channel marketing campaign to acquire new customers. If you spend enough money you’ll get a decent number of conversions for your media spend, but not all consumers will be of the same value to your brand. 

Some women will discover your brand’s shoes and become instant aficionados who can’t stop talking about them on Instagram. Another may buy a pair of your super high-end shoes solely because she’s in a wedding party and the bride told her she must wear them. Others will see your ad, buy a pair for work, decide they’re a great value, and will go on replenish them year after year. They’re not aficionados by any means, but loyal nonetheless.

Using this new mindset will allow us to:

• Eliminate consumers who have no interest in high-end shoes so you don’t spend precious media dollars targeting them
• Identify the enthusiasts who have the propensity to become a brand ambassador
• Identify the replenishers, and create a loyalty program that encourages them to replenish once a quarter rather than once a year.
  

No persona or demographic attribute will allow you to distinguish between these types of buyers.

Data Illuminates the Journey  

No doubt you are sitting on a giant pile of data and within it lies incredible insights into how consumers interact with and respond to your brand. How do you start to deploy it?

Begin by using your data to stitch together cohesive journeys. Probe your data to ask the following questions: 

1. How did each customer segment arrive at your site?
2. How many times did they visit before making a purchase? 
3. How much time elapsed between the initial ad view and conversion? 
4. How many ads did they see before converting?
5. Which ones did they see?
6. In which channels did they see those ads? 
   

Post conversion, you can continue to gain insights that will help you bucket customers in order to create custom initiatives and rewards programs for each cohort. For instance, compare the customers who needed some kind of a promotion in order to make an initial purchase from those who bought at full price. How did those journeys differ? How frequently does each group purchase?  Which ones share your product images on Instagram or pin them on Pinterest? 

Identifying each of these journeys will enable you to suppress promotions from those who don’t need a discount, reserving them for those prospects who need an extra incentive to convert and will ultimately have a high lifetime value.

These are all knowable answers, and it’s well worth your time and effort to parse your data pools. Invariably you'll see multiple consumer journeys emerge that will provide a roadmap for customizing the customer lifecycle to cement the relationship. You’ll know how to distinguish between brand enthusiasts, occasional shoppers, and one-and-done customers, and engage with them appropriately.

Additionally, you’ll learn which ad formats and channels are absolute requirements in order for each category of prospects to proceed through your customer journey. Let’s say you invest in video ads because we all know that the combination of sight, sound, and motion is a great way to tell a brand story. But video is super expensive. An analysis of the customer journey will tell you which consumers need to see a video ad -- along with where and when -- in order to convert. So rather than spend half your media budget on spray-and-pray video ads, you can focus this valuable resource on the consumers and scenarios where it will do the most good.

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One Customer, Multiple Journeys

When I talk about illuminating the journey I don’t mean just the purchasing journey. Your relationship with your customer should span their:

• Acquisition journey
• Repeat purchase journey
• Reactivation journey
• Conversion to loyalty/advocacy journey
• Product replenishment journey
  

Every step in the customer life-cycle involves a journey that can be analyzed and activated to deliver better marketing outcomes. 

In fact, these subsequent journeys are even more illuminating because they’re your customers, meaning you have first-party data on them. You have every right to analyze their behavior without running afoul of GDPR or CCPA. And the insights you’ll get are rich and highly nuanced, which you can use in interesting ways.

I’ll give you an example. I once worked for a luxury men’s fashion label that was known, in part, for its denim. We wanted to prompt repeat purchases and so we looked at our customer’s past denim purchases, selected jackets and other accessories that went well with them, and used those pairings as the creative assets for a highly targeted digital campaign. We didn’t go the creepy route of saying, “this jacket will match the denim you already purchased.” Instead, we just showed a nice pairing of the denim with the brand’s new arrivals. Thanks to that data-driven insight, the campaign delivered phenomenal results.

The bottom line is: marketing, advertising and sales are all about influencing a consumer’s behavior, why not let their behavior drive how you engage with them? Every part of every journey within the lifecycle is knowable. Just look at your existing data and build your strategies based on what you see.

Use Data to Develop a New Set of Success Metrics

Your data will also provide a more useful set of metrics for understanding your customers and what you can reasonably expect from them. 

Ask your data: 

1. What does a new customer look like within the first 90 days of acquiring him or her? The first 12 months? 
2. How does the loyal customer’s behavior differ from a one-and-done or occasional buyer?
3. Did the channel from which I acquired this customer lead me to a better long term outcome/LTV than others?
   

How do you define what loyalty means for your brand? A high-end luxury brand may deem a customer who buys twice a year as a top-tier loyalty member, whereas a less expensive brand may need to see at least four to six purchases annually in order to consider them loyal.

An examination of your data will allow you to set benchmarks that are appropriate for your unique customer base. More importantly, it will allow you to distinguish a truly VIP member from someone who shops frequently, but only during big discount periods, as those customers should likely be messaged differently.

What’s Stopping Organizations from Being Truly Data-Centric?

Every brand has the data they need to transform the ways they assess, engage, and service their customers, and the market offers plenty of tools for putting that data to good use. So what’s stopping them? It really comes down to culture. Silos still exist, and a truly customer-centric, data-driven approach isn’t possible until those silos are eliminated.

One way, and perhaps the best way, to eliminate those silos is to align each department around a set of goals. For instance, instead of viewing IT as an expense in the P&E, consider it a resource to help the CMO understand the best ways to use technology in service of increased sales. The finance team spends its days looking at revenue and expenses, which means it’s in a unique position to identify brewing issues and opportunities, like higher than normal product return costs or better ways to optimize retail outlets to maximize revenue potential. 

Every employee can do his or her job better when data drives your company’s understanding of the customer and working towards the same goals.

As brands confront whatever this pandemic has in store for them, it will be well worth your time to leverage this royal asset your company is sitting on. Data is king, as long as you use it to drive your next moves. You have it in abundance, the time has come to effectively operationalize it. This is the job of the entire kingdom, not just the royals.