Questions I’m Bringing to TDWI Orlando
TDWI Orlando is answering some hard questions about how analytics professionals will continue to add value for stakeholders and accelerate growth. Here are the questions I’m bringing next week. Looking forward to finding some answers. I’ll follow up afterward and share what I’ve learned, so follow the blog if you want to find out!
What Metrics Matter?
Every successful business knows its core KPIs and where they need to be on a weekly/monthly/quarterly cadence to reach the organization’s goals.
Measuring a key metric over time is table stakes.
Who are the key contributors to your KPI number, who or what is driving the current trend? What seasonal trends provide tailwinds to reaching your goals, which provide headwinds. I want to see techniques for finding trend drivers. How can we turn higher-order statistical analysis into actionable workflows for business intelligence workers? Make them accessible or productized in a way that more and more employees can extract value from their data?
Personalization vs Performance
Artificial intelligence and its principal application, machine learning, are the buzzwords du jour in analytics, but it is still too hard to explain the value it can bring to your organization.
Machine learning has found two major business applications: personalizing experiences for end-users (“You might also like…” from Amazon, Netflix, Spotify) and performance improvements to a specific task (Email spam filtering, Facial and Entity Recognition to organize photos, analyzing Traffic patterns to improve navigation).
B2B applications for machine learning include measuring purchase intent of digital visitors in real-time, based on their behavior. CRM giant Salesforce is trying to do similar things with customer data using its Einstein application.
Google, Netflix, Amazon, and Spotify have trained customers to expect ever-higher levels of personalization and ever more accurate predictions.
For the companies and industries not listed above, how can marketing and analytics teams bring applied machine learning in-house? Are they looking for custom-built solutions? Vendor applications? Ad-tech or inbound marketing / digital experience?
And building it is one thing, but the leadership wants to see an ROI, how do you show an ROI from your analytics / big data programs?
It’s Still a Dashboard World
Making data actionable is a pretty good raison d’etre for any analytics team IMO. Visualizations are extraordinarily powerful mechanisms to communicate the health of a business, and where to find the fires that need fighting and the opportunities that need seizing. Here are some of the dimensions that matter in dashboard design, and questions to answer:
