As consumer understanding of how important controlling their personal information grows, they are increasingly taking control of it. Not just limited to protecting information about themselves and their families, their demand for rights and protections are extending to their possessions and expanding their rights as to who can access their data and under what circumstances.
The new shopping dynamics have also cast a spotlight on the inadequacies of many brands’ online customer experience and the ineffectiveness of generic retention programs. In many cases, brand-customer relationships proved to be based more on habit than true loyalty or brand affinity. Until marketers create a more relevant experience where, when, and how customers want it, they will struggle to get customers to return to their brands, and will leave the door open for lower priced and easier to find brands to build relationships with their former customers.
The need for an effective data strategy has never been stronger. Faced with years of increasing competitive pressure from diversified businesses like Amazon, and now an unprecedented economic downturn, more businesses are looking to emulate what has allowed Target and Best Buy to successfully fight back. Strengthened by their existing data strategies that helped build stronger and more informed customer relationships before Covid-19 hit, they are now doubling down on their data strategies to take advantage of new opportunities while their competitors struggle to adapt.
We have provided our take on key aspects of the regulations California has released to help businesses comply with CCPA (California Consumer Protection Act).
Marketers are always looking for a competitive edge, the next new thing that will improve customer engagement, or just a better way to execute existing communication programs. To that end, we’ve outline three data attributes that nearly all B2C and B2B marketers can employ for targeting (or exclusion), content, and reporting purposes. Each of these has proven to be effective at improving communication performance and the customer experience, while reducing attrition.
To help you approach testing from an objective and technical perspective we have put together a framework and sample size calculator. Together these should help you create more credible tests that get at the heart of what you are trying to accomplish with testing and produce better insights.
Turning your Big Data into actionable data is a challenging but rewarding process. As with many things, the first step is often the most difficult. Following the process we have outlined here, marketers can start to lead their organization down the path to becoming a data driven one.