How to Build Customer DNA with Self-Identified Data
Consumers’ desires, motivations and preferences directly influence 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 personalised. Although brands spend over $60B on marketing technology, 63% of marketers say their customer data is incomplete. This blog will explore how to build customer DNA with self-identified data.
How to understand customers at scale but also at an individual level?
To completely understand 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 Storing and analysing high quantities of behavioural and transactional data, such as products viewed/purchased/returned, device used, location, visit frequency/duration/channel/medium. Analysing these metrics regularly and drilling down to individual customer levels helps a brand to have a better general understanding. This can be used to create high-level segments.
To have a complete grasp of its customer base requires a brand to take one step further tough. Step 2: Establish a relationship with customers, engaging with them regularly and learning from them. If supported with a mutually beneficial value exchange, this leads to the customer’s voluntary sharing of data about themselves and their needs. We call this self-identification of customers and make 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 an excellent example from the article ‘What do Prince Charles and Ozzy Osbourne have in common?‘ at BBC.com.
We’d all agree that Prince Charles and Ozzy Osbourne have very different characteristics. That being said, here are a few features that these two gentlemen share:
Born in 1948
Married & Re-married
Live in London
Like to travel and drink wine
For a business that only relies on high-level demographic data + behavioural data, it would be challenging to place them as part of different customer personas. Showing them the same ad would be inefficient because they share these characteristics.
Creating a Customer DNA chart is an excellent exercise for shaping complete and accurate customer profiles relevant to your brand and business.
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 individual 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 could be used to improve the quality of service or precision of communication a customer receives. Depending on the size and type of business, the DNA can be more complicated or simple. Above is an example chart consisting of example categories.
A brand should collect and segment customers using behavioural and transactional data. Still, 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 and asking the right question elegantly and with fun is the key. Also, don’t forget that most customer DNA characteristics are not static; they change over time. Engaging customers regularly also makes it possible to validate previously recorded characteristics.
Relying solely on transactional data and profiling me as a ‘parent’ would be a mistake. If a customer is buying baby products, wouldn’t it be nice to know the reason for that purchase? I may be buying a gift for my 5-year-old niece…
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 a company. Or if we could know the current mood of the subscriber, maybe one could make much more accurate recommendations.
Ad targeting and precision are important issues for products mainly sold offline, 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 it all year long. The best way to do this without transactional data is to simply ask.
There are also some characteristics that, when discovered or metrics 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. Understanding the reason for churn in that market is valuable; without direct communication, it’s impossible to know the exact cause.
Similarly, say a loyal customer of a pet food brand is churned, and they would want to know why. If the answer is about the nonexistence of grain-free cat food, they may want to take action.
Criteria for Success
Having a complete customer DNA-focused approach should trigger many micro KPIs that should be measured periodically, such as; ad relevancy, brand recall and CTR for external communications, the 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 lifetime value.
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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