Making data-driven marketing decisions
The question I, and other data strategists, get asked all the time is, “How can I use data to make smarter media decisions?” Often there is a measure of frustration behind this question. Organizations have been gathering more and more data over the past ten years, but many leaders still don’t feel they are getting “value” from that data.
The results from the NewVantage Partners 2019 Big Data and AI Executive Survey show where many companies (including 65 of the Fortune 1000) see the largest gaps.
72% of survey participants report that they have yet to forge a data culture
69% report that they have not created a data-driven organization
53% state that they are not yet treating data as a business asset
52% admit that they are not competing on data and analytics.
The percentage of firms that identified themselves as being data-driven has declined in each of the past three years from 37.1% in 2017 to 32.4% in 2018 to 31.0% this year
In my years of experience working with marketing organizations, I’ve found most are not as diligent with data as they are with media investment. The maturity of media planning and buying platforms has increased rapidly, but those platforms are ultimately only as good as the data being used to power them. Here are four things companies should be doing to make sure they are building clean, robust data assets that deliver value in the media buying process.
Help shareholders see the value of data investments across people, technology, processes, and operating model beyond simple ROI. As implementation of data strategy can be lengthy, it’s important that your story encompasses the macroeconomic landscape, shifting consumer behaviours, and what is at risk if the company “does nothing,” or pulls the plug before realizing the benefits.
The converse of personalization has always been scale. Building a scalable data platform of consented customers requires a robust data collection and management operation. Once you know who they are, make every interaction count by delivering an omni-channel audience strategy and personalized customer experience.
Many organizations are built with teams in vertical silos - maintaining their own P&L, tools, and data sets. This creates disparate data owners and gate keepers who can be protective of their assets. Building an organization that is data-centric means that data is democratized, freely available (with the appropriate security), and understood - so that anyone, not just an analytics team member can query and make use of data.
Finally, it’s important to foster a culture that is comfortable sharing data across departments, agencies, and consulting partners. A lot of investment has gone into building customer profiles across your data platform, but true omni-channel strategies are only possible if all players can align on a single view of the customer.