Power Tools & Hardware
Bunnings Australia
A power tools brands marketing team was receiving consistently positive aggregate review scores across their product line but field sales reps were hearing complaints about a specific cordless drill model in certain regions. The brand had no systematic way to analyze review sentiment at the regional or store level. They were relying on quarterly manual review reads that sampled a fraction of actual feedback and took too long to produce to be actionable.
Intodats sentiment analysis tracked reviews at the store and postcode level across the brands full product portfolio — breaking down sentiment by category, product, and geography. Weekly AI-generated reports surfaced the most common themes in both positive and negative reviews, with regional breakdowns that matched the brands sales territory structure. For the cordless drill model in question, Intodat identified a cluster of negative reviews in three specific postcodes mentioning battery connection issues — a pattern invisible in the national aggregate score.
The brand escalated the battery connection issue to their product team within two weeks of deploying Intodat — months ahead of when it would have appeared in their standard quarterly review cycle. A targeted product inspection and silent fix was implemented before the issue spread to other regions or surfaced in national media. The marketing team also used regional sentiment data to brief field sales reps with territory-specific competitive intelligence improving sales conversation quality and close rates. The brand now runs weekly sentiment monitoring as a standard part of their ecommerce operations.
The real problem was not the product defect — it was the delay. The brands quarterly review process was designed for trend analysis, not operational response. By the time an issue appeared in a quarterly report, it had already affected hundreds of customers and potentially thousands of purchase decisions influenced by those reviews. Intodats approach — weekly AI analysis, regional segmentation by postcode and store, category-level breakdowns — turned review data from a lagging indicator into a leading one. The battery connection issue was caught early precisely because Intodat was looking at store-level sentiment, not just national averages. Regional clustering is often the first signal that a product issue is real and localized before it becomes a brand-wide problem. For a brand operating across a large national retail network with significant regional variation in usage patterns, this level of granularity is the difference between managing a product issue quietly and managing a PR crisis publicly.