Posted: Monday 4th December 2017 in Analytics and tracking, Retail Strategy, Technology, Thought Leadership.

In an increasingly data-rich world, there really is little to no excuse for not measuring the effectiveness of your marketing activity. Whether it’s digital display, direct mail or a PR campaign. In a world of predictive modelling and machine-learning, there’s still a lot to be learnt from your previous performance. But how do you know if what you are measuring is useful and reflective of reality? A common trap is to focus too much on hard sales measures. A lot of marketers are obsessed with ROI, and whilst this is useful for identifying high-level success or failure, it does little in helping you to understand “WHY” a campaign performed as it did. (It’s perhaps also reflective of how some marketers are more interested in proving they’re doing a good job, rather than actually doing a good job, but that’s a discussion for another time!). Which customer segments were most responsive? Which creative was most engaging? Was your uplift driven by weight, or frequency of purchase? These are the kinds of questions you should be asking to make your next campaign even more successful.

Quite often you should know the questions you want to ask your analysts before the campaign has even begun. They should be linked to the original objectives you were trying to achieve. In my experience, setting and understanding clear objectives is vitally important when trying to understand the success of a campaign. All too often I hear people tell me the objective of their campaign is to drive sales. Of course, this is the overarching objective of all marketing activity; to make it more likely that customers will buy your product. However, your campaign objectives should reflect “HOW” you plan to achieve this. Are you looking to trade customers up to a more expensive product? Is your goal to increase market share, and out-perform your competitors? Do you want to target and activate customers from a particular segment or demographic? If you understand how you want your customers to respond to your campaign, it is easier to define which data points to analyse and monitor campaign success.

Focusing on your customers and their behaviour is crucial to effective campaign measurement. Profit, margin and ROI might be good for keeping accountants happy, but it’s customers who are viewing your ads and (hopefully) purchasing your products. This is where advancements in data and science are giving retailers the competitive edge. Customers have never generated as much data as they do today: loyalty cards, cookies, geo-location, eye-tracking studies, primary quantitative research – combine these together and you will have a rich understanding of what your customer has seen on their purchase journey and how they’ve responded. Add in some very smart analysts and statisticians who can tackle this complex, multivariate problem, and you can start to measure the impact your marketing is having across multiple channels and campaigns. From there your questions move from tactical to strategic, and you’re a long way ahead of your competitors.

Finally, good campaign setup and execution goes a long way to ensuring accurate and timely results. Do you need to select a control sample? What requires A/B testing? Getting your analysts involved early in the planning process and working together on the “experimental design” of a campaign will mean you won’t get disagreements about methodologies and accuracy of results. This will speed up recommendations you want to take forward in your next activity. It may seem like less of a priority amongst all other logistical and operational hurdles, but failing to plan how you measure marketing activity, could lead to you measuring the failure of your retail strategy.