RIS/CGT: How can technology help brands operate in the ‘new normal?’
Chapo: Brands will need to continue to invest in technology that enables personalized, seamless omnichannel experiences for their customers, while providing flexibility in how the customer chooses to interact with the brand. Brands must simultaneously recognize the fundamental shift in customer data privacy that is happening. Given these conditions, savvy brands are increasingly leveraging their rich first-party customer data, including preferences and purchase history, to power personalized experiences at scale. A core technology many are investing in is a customer data platform (CDP). The CDP allows the brand to develop a trusted 360 view of the customer, develop significant and actionable insights, and power exceptional experiences. Other technologies built on top of this foundation must enable a brand to quickly, easily, and accurately create new experiences to continue to exceed customer expectations.
RIS/CGT: What are some of the myths brands face when looking into data/analytics tools and technologies and how would you debunk those?
Chapo: Myth #1: Technology alone will solve the problem. Too many brands focus on features and not the overall partnership and long-term business plan to drive continuous growth.
Myth #2: All platforms keep you in control of your data and your ecosystem. The truth is that many vendors providing data and analytics capabilities are designed for lock-in and to wall off data or limit your ecosystem based on their best interest.
Myth #3: Any system can handle the scale/complexity of the data at the speed required. Many solutions are not designed to facilitate the hundreds of billions of rows of data that need to be crunched to arrive at the views, analytics, or segments needed. This leads to decisions centered around the technology instead of the strategy — like truncating data sets or massive latency waiting for reporting that arrives so late you can't use it to optimize in the moment.
Myth #4: Identity is a commodity feature and it's all the same. Brands often pay attention to the output parts of their solutions — the fancy dashboards, the predictive models, the journey — all super important. But they fail to pay attention to the quality of customer records and identity which means often leaving data silo'd, limiting reach, getting customer insights and attribution totally wrong, leading to bad business decisions or stalling initiatives. These behind-the-scenes capabilities are make or break in any modern analytics capability and there are rampant data quality issues sabotaging many of the best laid data-driven analytics projects.
RIS/CGT: What best practices would you offer brands that are starting or upgrading their analytic-investments?
Chapo: As a practitioner who has helped build analytics capabilities across several brands, one of my biggest pieces of advice is to leverage technology partners along your analytics journey, as the natural tendency is often to build everything internally. While every brand does have a unique set of data and customer challenges, more often than not these have already been solved by others. Think about using the time it takes to drive business and customer impact when evaluating whether you should build something yourself versus buying a solution. Another best practice is to approach these investments as both delivering a technical capability as well as effectively integrating these capabilities into the day-to-day business operations. Without this focus on change management, these analytic investments can be at risk at becoming an interesting project that delivers minimal value to the organization.