Data & Analytics
The Power of Big Data Relies on Bold Strategies
Big Data arrived with the promise of making geniuses out of marketers. Abundant consumer data was going to lead to better targeting, stronger connections, and indisputable ROI. So, what happened? Why are we still looking for new ways to prove our marketing’s impact, and why haven’t we reached a unanimous consensus on the best way to make Big Data work in our favor?
By now, every marketing organization, agency, and administration has heralded a “Big Data” Initiative. While these algorithms generally provide marketers a mass volume, variety, and velocity of real-time data to improve customer experience and drive marketing impact, they sometimes fail to work as intended. That is the price marketers pay when their strategies aren’t customer-centric.
Many of us have rationalized a marketing technology solution – demand-side platform, data management platform, dynamic creative optimization, marketing or sales automation platform, etc. – with a model that shows exponential return on advertising investments. If you’ve turned that model into reality, give yourself a hand. Research says you’re likely a leader who leverages first party data, aligns your media metrics with business outcomes, and encourages strategic experimentation. That’s good because the rise of of AI and Machine Learning leaves us the much simpler opportunity in 2018 to be smarter with data, no matter the size.
Today’s technology is more complex than the tools of the past, but the guiding principles for your data remain the same. The information you collect is worthless without a plan to properly utilize it. When navigating the world of Big Data, don’t lose sight of:
Focusing data strategies on business impact
At the end of the day, your customers are not following a perfect purchase funnel and one banner in one channel or one search result is not the single influence on purchase. To rationalize marketing’s impact as such is flawed, redundant, and headed for diminished returns. Now is the time to step outside your comfort zone and hold your digital work accountable to true business drivers as KPIs – leads, sales, customer engagement and retention, rather than channel specific reach, impressions and clicks.
Putting the customer in the center and hunkering down for a long ride together
A customer-centric approach for data aggregation, with a vision for omnichannel attribution, will accelerate your path. All touchpoints your identifiable and prospective customers engage with across your owned, earned, and paid ecosystem are valuable data points to consider for segmentation, evaluation, and modeling to drive business impact. Stay committed to the customer experience, rather than the channel performance, and agonize with your channel teams to set a realistic attribution window to see success in digital.
Collection is only half the battle. You must be prepared to learn from your data, work with internal teams to optimize efforts, and be willing to experiment. Here are a few tools and approaches we use with our Edelman clients to apply Big Data best practices:
It is always necessary to map ROI of marketing efforts to business goals, against which to allocate investments, see impact, and take the right actions to drive growth. The measurement framework connects the business objectives (which usually map to some category or customer behavior change) to Key Performance Indicators the business uses to measure these objectives. Where there are no direct data links between digital advertising and business impact, build models that measure real time metrics to sales influence or qualified leads, for instance. Ultimately, these frameworks inform data, technology, testing, and reporting strategies to tell consistent stories of each tactic against business impact.
Find your first party data, who is using it, how it is captured and stored, and leverage it to inform holistic requirements against which to select vendors for your data lakes, DSPs, DMPs, DCO, personalization, marketing and sales automation solutions. Use humans to derive insights from your data to inform customer-centric content strategies, then identify gaps to fill with third party data and to measure impact to your measurement framework.
56% of leaders say their organizations dedicate time and budget to strategic experimentation. That means many marketers are still uncomfortable with signing up for and committing to testing programs. Testing allows us to build those muscles with a system where you have wins and losses, all geared towards the key performance indicators. Measurement frameworks give us a strategic roadmap to build out Learning Agendas and rigorous testing programs. Tools like Optimizely and Adobe Target can be leveraged at scale. As mentioned, the critical attributes for a testing program to be a success are measuring real time test performance to business impact (not just channel KPIs). Also, do not overlook allocating an insanely curious team to maintain testing governance, prioritization, and insights to interpret results regularly and against your creative, budgets and measurement strategy.
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