CMOs, like myself, always want to better understand our current and potential customers so that we can set the direction of our business to respond to, engage with, and ultimately provide the best possible products and/or services to our customers.
Originally, our customer information was sourced through focus groups and qualitative and quantitative market research, but, these sources are being supplemented by newer and more accurate sources of customer insight through data from virtually every consumer touch point. This has led to many focusing on the importance of “Big Data”, which has wrongly given the emphasis to the data itself as the end goal, rather than the requirements of the data and the insights it can provide.
Most companies out there are aware of the potential value of their data, but for some, unfortunately, the actual value will not equate to the potential as data often gets stored in silos and there is a tendency for many companies to feel that the hard part is done once they have started collecting and storing the data.
In reality, there are two fundamental challenges that we as CMOs need to overcome if we are to truly tap into the value of data. First, there needs to be much more focus on starting with the business question at hand and the desired results. Start with the KPIs you need to drive. Then decide which lifecycles need to execute those KPIs – and then your data teams can figure which data sets from which sources are required.
For example, we’ve taken this approach at Aimia with several of our grocery clients globally, including Sainsbury’s in the UK and Coles in Australia, to optimize their digital flyers. Previously, an email was sent to customers each week telling them about the “biggest and best” promotions out of the thousands of deals in store that week. Click through and open rates were lower and cost per redemption higher and relevancy and opt outs on the wane. They had specific KPIs they wanted to drive and a specific lifecycle program to do the driving. Our clients’ aim was to move to a more targeted and personalized communication which would tell people about the specific promotions of interest to them, potentially bringing them into the store. We realized that focusing on the SKU-level transactional data would be the best data set to answer this challenge. So a customer who never buys soft drinks would not hear about the latest pop promotion in their message, but they would hear about the top 6-10 promotions most likely to get them in store.
The second challenge that CMOs need to consider is how to integrate different datasets to provide a single customer view. Often this will include the breaking down of silos rather than setting up new data feeds, and this will involve the typical business challenges of inertia, complexity and the need to have a sufficient business case. The good news is that the marketing platforms and technology today not only exist at all levels, but they are fully integrated and readily available. Additionally, the costs associated with storing data and copying other data sets into a master database as well as extraction capabilities and speed for right time usage have been greatly reduced in recent years. This makes the exciting possibilities of one-to-one marketing and increased relevancy a tangible reality.
By focussing on insights first, we as CMOs can narrow down what data is ‘important’, allowing us to collect, store, and analyze only what we need to create those ever important personalized and relevant customer interactions – keeping results and ROI achievable.
John Boynton is the chief marketing officer of Aimia Inc.
