marketing effectivenessWhen speaking about the power of converging different technical disciplines to yield customer insights, it’s common for the conversation to focus on converging analytics & research for proposition insights. But what about measuring your marketing effectiveness?

Another rich territory for seeing the benefit of multiple technical customer insight (CI) disciplines is the measurement of marketing effectiveness.

In this short overview, we’ll review the ways both analytics & research provide inputs needed for a more holistic view of your overall marketing effectiveness.

One of the reasons for needing to call on the skills of two complementary CI disciplines, is the need to measure different types of marketing spend. The most obvious example is probably the challenge of measuring the effectiveness of “below the line” verses “above the line” marketing.

For those not so familiar with this language, born out of accounting terminology, the difference can perhaps be best understood by considering the ‘purchase funnel‘.

Most, if not all, marketers will be familiar with the concept of a purchase funnel. It represents the steps that need to be achieved in a consumer journey towards making a purchase. Although often now made more complex, to represent the nuanced stages of online engagement/research or the post-sale stages towards retention/loyalty, at its simplest a purchase funnel represents four challenges. These are to reach a mass of potential consumers and take some on the journey through awareness, consideration and preference to purchase. The analogy of the funnel represents that fewer people will progress to each subsequent stage.

Purchase Funnel.001

Back to our twin types of marketing. Above-the-line marketing (ATL) is normally the use of broadcast or mass-media communication to achieve brand awareness & consideration for meeting certain needs. Getting on the ‘consideration list‘ if you will. Traditionally this was often TV, radio, cinema, outdoor & newspaper advertising. Below-the-line marketing (BTL) is normally the use of targeted direct marketing communications to achieve brand/product preference and sales promotions. Traditionally this was often direct mail, outbound calling & email marketing. In recent years many markers talk in terms of “through-the-line” (TTL) advertising, which is an integrated combination of ATL & BTL messages for a campaign. Social Media marketing is often best categorised as TTL, but elements can be either ATL or BTL, largely distinguished by whether or not you can measure who saw the marketing and have feedback data on their response.

Let’s return to the theme of using multiple CI disciplines to measure the effectiveness of these different types of marketing. The simpler example is BTL marketing. Here the data that can be captured on both who was targeted and their behaviour following enables the application of what is called the experimental or scientific method. In essence the skills of Database Marketing teams, to set-up campaigns with control cells & feedback loops. To merge the resulting data and evidence incremental changes in behaviour as a result of the stimuli of marketing campaigns and optimise future targeting.

ATL marketing is more of a challenge. Because control cells do not exist and it is impossible to be certain who saw the marketing the comparison needs to be based on time series data. Here the expertise of Analytics teams comes to the fore, especially Econometric modelling. This can be best understood as a set of statistical techniques for identifying which of many possible factors can best explain changes in sales over time and then the ability to combine these into a predictive model that can predict future sales patterns based on those inputs. There are many skills needed here and the topic is worthy of a separate post, but for now suffice to say that analytical questioning techniques to elicit potential internal & external factors are as important as modelling skills.

Hopefully you can see that my definition of today’s TTL marketing campaigns thus necessitates making use of both Database Marketing and Analytics team skills to measure marketing effectiveness. But beyond this simply being a division of labour between ATL elements being measured by analytics teams & BTL by database marketing ones, there is another way they need to work together.

Reaching the most accurate or helpful marketing attribution is an art as much as a science. In reality, even BTL marketing effectiveness measurement is imprecise (due to the complexities of media interdependencies and not knowing if the consumer really paid attention to communications received). In a world where your potential consumers are exposed to TTL marketing with omni-channel options of response, no one source of evidence or skill set provides a definitive answer. For that reason, I once again recommend convergence of Customer Insight evidence.

Marketing Attribution convergence.001Best practice is to garner the evidence from: (a) incremental behaviour models (econometric or experimental method); (b) sales reporting (reconciling with Finance numbers); (c) market position (research trackers); (d) media effectiveness tracking (reconciling with behaviour achieved throughout purchase funnel).

Converging all this evidence, provided by data, analytics, research & database marketing provides the best opportunity to determine robust marketing attribution. But do keep a record of your assumptions and hypotheses to be tested in next campaigns.

I hope that was helpful. How are you doing at measuring the effectiveness of your marketing? I hope you’re focussed on incremental profit not ‘followers’.