Delivering Insight In Consumer Marketing

What do B2C marketers want to do? Talk to people. But specifically, they want to deliver relevant messages that resonate with their target audiences, and they want to do so in the places where they will make a difference. Even the greatest creative in the wrong place is essentially worthless after all.

As an objective that seems straightforward enough. But there is one central challenge in the way of making it happen. In many cases knowledge of the end customer is patchy or incomplete at best. Sure, many brands have successfully moved towards a direct digital relationship with the customer, but that model remains the exception rather than the rule. Perhaps 20 to 30% of sales are direct to consumer - and in those cases we can begin to build a picture of each customer as an individual.

In the traditional retail environment, however, brands are still at one remove from the consumer. In order to develop a clear understanding of our target audience - their likes, their attitudes, what they read, where they go - they must continue to rely on the chinese whispers of conventional market research.

Using the various techniques of market research the brand can usually gain some general understanding of what a typical consumer looks like - but can’t go much further than that. Increasingly that isn’t good enough.

Why Brands Need More Insight Than Ever

Before answering that question I’d like to briefly draw attention to my use of the word ‘insight’ rather than ‘data’ in that sub-heading. Although it has become fashionable to talk about how centrally important data is to modern brands and businesses, the truth is that data in and of itself is worthless. It is fantastically easy to collect and fantastically difficult to make much sense of, or at least it is in most cases. That’s why there remains such a huge disconnect between the amounts of data available to us and the smartness of the typical marketing campaign.

Insight, on the other hand, makes a difference. And today more than ever, where so many purchases are influenced by a complex network of groups, individuals and brands - each with their own messages - it is vital to understand this network of influence in order to successfully talk to the right audience, in the right way, and in the right place and time.

To do that means having true knowledge relating to this network, and it means being able to categorise and classify customers into meaningful groups. If we do that successfully, we’re able to customise our communications, find commonalities between customers, pay special attention to influencers, and deliver new levels of relevance and effectiveness to our communications across the board.

The DataChemist Approach

That’s where we come in. Our customers are able to integrate data from multiple sources to deliver a clear, structured understanding of the consumer at an individual level. Whilst we understand their purchasing behaviour, we are also able identify clear groupings around shared attitudes and behaviours, and in turn understand how best to talk to them as groups and individuals.

Perhaps more importantly, we are able to quickly identify where data is missing, and help our customers find and evaluate new data sources that fill in any blanks that currently stand in the way of broader customer insight.

We are also able to clearly understand and model how influence works across the customer network. Which groups or clusters influence others? How does that influence flow between them, and how best can the business encourage it or provide content and creative for influential groups to share? Insight relating to these questions separates those organisations who really understand retail in the age of social media and those who do not.

Lastly, the ability to rapidly match individuals according to patterns of behaviour gives new power to real-time recommendation engines. With DataChemist, it is possible to match customers in an instant, and by doing so understand what is next - or likely to be next - for any one of them. That ability to evaluate propensity in the moment delivers more accurate, relevant and effective recommendation engines - and more compelling marketing communications.

The end result is greater brand loyalty, greater share of wallet, and most importantly of all: greater revenue.

Written by

Kevin Feeney


September 14th, 2018

Share this post:

Suggested Posts

Understanding RDF Understanding RDF Understanding RDF

Technology, Data

Understanding RDF

Posted April 23rd, 2019 by Kevin Feeney

Read more

Answering The Really Big Questions Answering The Really Big Questions Answering The Really Big Questions

Technology, Data

Answering The Really Big Questions

Posted March 25th, 2019 by Luke Feeney

Read more