How to Build Customer DNA with Self-Identified Data

The desires, motivations and preferences of consumers have a direct influence on a brand’s marketing strategy and service offering.   The dream of all marketers is to know their customers better and provide a customer experience that’s relevant and personalized.  That being said; although brands spend over $60B in marketing technology, 63% of marketers say their customer data is incomplete.

Source: TheDataIQ, BDO

How to understand customers at scale but also at an individual level?

In order to have a complete understanding of a customer’s characteristics and needs, sufficient and high quality data is crucial.  We went through different types of data you can have on your users in our blog post:  A simple guide to data types for marketing.

Step 1 is storing and analyzing high quantities of behavioral and transactional data; such as products viewed / purchased / returned, device used, location, visit frequency / duration / channel / medium and so on.  Analyzing these metrics regularly and drilling down to individual customer level helps a brand to have a general understanding and can be used to create high level segments.

To have a complete grasp of its customer base and business requires a brand to take one step further tough.  Step 2: establishing a relationship with customers, engaging them regularly and learning from them.  If supported with a mutually beneficial value exchange, this leads to the customers voluntary sharing of data about themselves and their needs.  We call this self-identification of customers and makes it possible for a brand to create detailed persona driven customer segments.

Relying solely on behavioral and transactional data is not enough.  To know why, rather than what is a big power.

Here is a great example that we love from the article ‘What do Prince Charles and Ozzy Osbourne have in common?‘ at BBC.com.

I think we’d all agree that Prince Charles and Ozzy Osbourne are two individuals with very different characteristics.  That being said, here are a few features that these two gentlemen share:

Both Male,
Born in 1948
Self-employed
Wealthy
Married & Re-married
Dog owners
Have children
Live in London
Like to travel and drink wine

For a business that only relies on high level demographic data + behavioral data, it’d be very difficult to place them as part of different customer personas and just because they share these characteristics, to show them the same ad would not be very efficient.

Customer DNA

A great exercise to shape complete and accurate customer profiles relevant for your brand and business is creating a Customer DNA chart.

DNA is a unique genetic code for each person and Customer DNA in the marketing sense is a complete profile for each customer consisting of unique preferences, motivations and desires.

Building a Customer DNA chart is like creating a ‘wish list’.  A business should identify and list all characteristics that if known would be valuable to the brand and in return could be used to improve the quality of service or precision of communication a customer receives.  Above is an example chart consisting of example categories.  Depending on size and type of business, the DNA can be more complicated or simple.

A brand should collect and segment customers using behavioral and transactional data but the way to complete the missing links in the Customer DNA is through direct customer engagement and self-identified data.

A Customer DNA built with Self-Identified Data: What do you want to know?

Doing so, asking the right question elegantly and fun is the key.  Also don’t forget, most characteristics on a customer DNA are not static, they change over time. Engaging customers regularly also makes it possible to validate previously recorded characteristics.

Examples:

If a customer is buying baby products wouldn’t it be nice to know the reason of that purchase?  I may be buying a gift for my 5-year-old niece…  Relying solely on transactional data and profiling me as a ‘parent’ would be a mistake.

Or let’s picture a subscriber to a video streaming service; wouldn’t it be nice to know if that user is consuming content alone or with friends or family?  Perhaps the consumption patterns are different when alone vs. with company.  Or if we could know the current mood of the subscriber, perhaps one could make much more accurate recommendations.

For products mainly sold offline, ad targeting and precision is an important issue as there isn’t a lot of online transactional data linked with consumers.  For an ice cream brand for example,  it’d be nice to split the audience between users that consume ice cream only during the summer and others that consume all year long.  Without transactional data, best way to do this is to simply ask.

There are also some characteristics which when discovered or metrics when changed, can and should trigger action.  Here are a few actionable insight examples:

Say a consumer goes Vegan and stops shopping from a market as they don’t offer vegan products.  To understand the reason of churn for that market is valuable, and without direct communication it’s impossible to know the exact reason.

Similarly, say a loyal customer of a pet food brand is churned and they would want to know why.  If the answer is about nonexistence of grain free cat food, they may want to take an action about it.

Criteria for Success

Having a complete customer DNA focused approach should trigger many micro KPIs that should be measured on a periodic basis such as; ad relevancy, brand recall and CTR for external communications, response rate for communications made internally across different channels, overall customer satisfaction and NPS, churn rate, up-sell value and so on; but the main KPI to track should be increased customer life time value.

About Poltio:

Poltio‘s platform gives brands the tools to gather first-party self-identified data through engaging interactive content, that can be used to build a detailed and complete Customer DNA. To learn more about how it works, visit Poltio.

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