5 Ways to Drive Evolution in Digital Analytics
Last month, at the inaugural Infinitive Digital BrainFest, some of the panelists and participants shared insights that got me thinking about where we are in the grand scale of analytics evolution. Many companies are still oriented toward fairly basic reporting and dashboards, which are tactical, backward-looking and explanatory of what’s already happened to and with your digital business. Still these tools are better than nothing and serve as an important foundation for more advanced practices – like harnessing big data to gain deeper and more current insights into business operations.
The long-term goal is to have tools and data streams to drive action that is more strategic in nature and more forward-looking because it’s based on predictive insights and recommendations. And if you can do it in real time, then you’ve evolved toward a pretty powerful analytics practice. There is a great deal of excitement across industries — from financial services to media and entertainment — about the use of predictive analytics to improve customer responses, raise conversion rates, and decrease churn.
While there’s no doubt that the future of digital analytics is faster and more predictive, that vision remains still a long way off for the majority of companies. So how do you get from here to there? We see five core strategies.
- Master the Basics: The funny thing about the basics is that you have to get them right. If you skip right over fundamental tasks (like configuring data streams for quality and ensuring your key performance metrics are aligned to top business objectives) to get to the supposedly “sexier” stuff (like advanced tracking, sophisticated testing and predictive analytics), you may not get the most out of your investments in tools and people. Mastering the basics gives you confidence and trust in your data, which means you don’t have to worry about second-guessing your data as you move toward more powerful models for using it.
- Don’t Overlook the Organization: Yes, analytics is heavily tool-centric and data-driven. But who uses the tools and digests the data? People, of course. Setting up the right analytics teams with the right skill sets (whether those skills come from within the organization or from outside consultants) really should be job one for analytics. Establishing the right processes to ensure the right people review the right reports at the right time (so they can make decisions with it) is another crucial success factor.
- Balance Science with Art: It is one thing to focus on all the “science” of analytics (crunching the numbers and querying data), but it is also important to appreciate the “art” of analytics” so that insights based on quality data can be shared and emphasized with various stakeholders. If your analytics team can tell a convincing story to key executives based on the data you capture and analyze, you’ll improve the likelihood that your recommendations will be put into action and that you’ll add value to the business. Plus, the analytics practice will gain credibility in the organization. Data-driven storytelling is especially critical for organizations that have cultures that accept or promote management by “gut feel.”
- The Power of Combination: True analytical power and predictive visibility comes from integration of disparate data sets. Site traffic, CRM, call center, billing, social platforms, survey results – all of these channels provide potentially valuable insights about individual customers, or even groups of customers. Organizations that can knit them together and cross-reference them easily will gain a much more complete picture of the business.
- Get Smarter Faster: In a fast-moving space like analytics, today’s cutting-edge innovation is tomorrow’s standard operating procedure. That’s why companies must continuously prioritize “deep dive” analyses and iteratively build upon them over time. The good news is that this can be done much more rapidly than before. The speed of feedback and results from digital business operations allows us to “fail fast” – test hypotheses, learn from them, iterate, and adjust our digital marketing campaigns or site offerings within hours and minutes, as opposed to days or weeks.