Our strategy included active AI development inside the product. If analytics and comparison move users from raw data to information, then AI helps move from information to insights and recommendations.
Problem 1
Research showed that 25% of clients, including an important management segment, run SWOT analysis during strategy planning. Manual SWOT is slow and expensive.
Solution
Generate SWOT analysis automatically based on mentions of the client brand and competitor brands.
Problem 2
Interviews showed that clients repeatedly use manual markup for advertising, WOM, opinions, and recommendations. This requires reading every mention and takes too much time.
Solution
Automate mention categorization and tagging, then expose those categories as first-class filters in the interface.
Problem 3
During expert sessions, we saw strong demand around anomalies in charts: spikes in mentions, engagement, and resonance. Analysts needed faster explanation of what happened and why.
Solution
Automatically mark peaks on charts and use AI to summarize mentions for a selected day or period, including peak analysis.
Problem 4
Industry experts highlighted that the key analyst job is generating insights and hypotheses from data, which usually takes 1.5–2 years of experience. Users also reported friction when adopting complex tools with dense interfaces.
Solution
Create a ChatGPT-based assistant inside the product, so users can request data explanations and idea generation through chat.
