Social.AI Categorizes Social Conversations
Like a Human
Then Predicts Brand Tracking KPIs
Like a Genius!
Stop Your Insights Drainage Today:
Better Brand Tracking at Lower Costs
C-Suites around the globe are asking for higher agility, real-time results, and cost efficiency at the same time. Can we replace survey based brand trackers with AI-generated predictions based on social listening data? The answer is an augmented approach called Social.AI
It estimates brand KPIs based on social data – realtime – for any niche you have or every brand and competing brand you track.
Our natural language processing engine automatically categorizes social conversations into content categories and our award-winning machine learning engine reliably predictes the in surveys measured brand tracking KPIs.
We put a dozen text analytics software systems to the test and found one that outperforms by far all in its accuracy. Its the technology of Caplena.com which we choose to integrate into the CX.AI platform. Caplena.com is a leading AI-aided platform for coding verbatim.
Social.AI Dashboards …
… describes the status
The dashboard reports the key metrics shares and visualizes its trend.
… visualizes key drivers
The key driver matrix has the frequency of mentioning a content theme on the vertical axis and the total impact (=importance) of such a theme as the horizontal axis. Topics with low frequency and high impact are typically those key success drivers that are usually overlooked when focusing on frequencies
… explains why measure changed
It happens after every wave of recurring surveys. Measures improve or decrease, and everyone immediately starts thinking “Why the hell …?”. What you need to do to explain the change in your measure is to look at those drivers that do have most impact AND significantly changed. This is precisely what the Explain Variance chart is doing.
… visualizes and explains
Our machine learning considers nonlinear and interactive effects, while conventional modeling only measures direct effects by assuming drivers are independent of each other. A common indirect effect in Social.AI models is those that drive the sentiment variable. The sentiment variable captures the emotional impact of every topic. With Social.AI those relationships are transparent at you fingertip.
… simulates actions and predicts outcomes
What is the exact impact of “very important”? Is it realistic to achieve the industry benchmark with a certain initiative? What will be the combined impact of a realistic set of improvements? To answer these questions, we implemented a predictor into the Social.AI dashboard.
