Defending market share against a competitor attack.
React in days, not quarters. Regain lost share before it spreads.
The situation.
Your quarterly sales reports tell you — a laundry detergent brand — that you have lost 2.3 share points across three major regions in Eastern Germany over the past three months, and offer no explanation. Meanwhile your competitor gains ground every week. By the time the brief reaches an agency, creative is developed, and a campaign goes live, another quarter has passed.
Why today fails.
The quarterly report shows the decline but not the cause. The brand team spends three weeks manually analysing data from multiple sources. The agency receives a brief five weeks after the decline was reported. The campaign launches ten weeks after detection. By then the competitor has consolidated their gains and the decline has spread to adjacent regions. Total time from threat detection to market response: 12–16 weeks.
How it runs end-to-end.
A step-by-step walkthrough of what happens inside the platform — and the value delivered at each step.
- 01
Detection — automatic, Day 0
AI Analytics detect the share decline within one week of it starting — not after the quarterly report. The system flags: "Brand share in particular Eastern German postcodes has declined 2.3 points in the past 8 weeks. This is outside normal seasonal variance. Alert level: High."
Value deliveredThreat detected 10+ weeks earlier than quarterly reporting.
- 02
Diagnosis — Brand Brain, 30 seconds
The brand manager asks Brand Brain: "Why are we losing share in these regions?" It queries retail sales, purchasing-power indices, brand health and competitive activity simultaneously and returns a contextual diagnosis: the decline is concentrated in 127 postcodes with PP index 75–90, where your pricing sits 22% above category average; a competitor launched a buy-2-get-1 promotion six weeks ago in the same regions; food inflation in those areas is running at 4.2%, driving trade-down behaviour; and your brand's value-for-money perception has dropped five points while the competitor's rose four.
Value deliveredRoot cause diagnosis in 30 seconds. Multiple data sources contextualised into one narrative. No analyst work required.
- 03
Strategy — Brand Brain, 2 minutes
Brand Brain generates a complete response strategy: target the 127 postcodes where share declined most (PP 75–95); audience = competitor switchers from retailer loyalty data plus the HyperPersona "Price-Conscious Family Shoppers"; channels = CTV (reach families at home) + DOOH near supermarkets in target postcodes + Social; creative = emphasise concentrated formula and value per wash; budget €180K over six weeks; measurement via clean-room sales attribution + brand health overlay; projected lift 8–12% in targeted postcodes.
Value deliveredComplete campaign strategy generated from data in 2 minutes — informed by retail sales, purchasing power, competitive activity and shopper behaviour.
- 04
Audience build — 5 minutes
Shopper IQ assembles the target: primary = competitor switchers (loyalty members who bought the competitor in the last 60 days but not your brand); secondary = Price-Conscious Family Shoppers in the 127 postcodes; exclusion = current loyalists. Total addressable: ~420,000 shoppers.
Value deliveredDeterministic audience based on real purchase behaviour — not "women 25–54".
- 05
Creative production — Brand Brain + Creative Intelligence, 1 hour
Variants are generated from the data-informed brief: A) "One cap. 30 washes. Half the cost per load." (value-rational); B) "The smart choice for families who know their numbers." (value-emotional); C) retailer-specific variant with price points near key stores. Sales Impact Predictor scores each — Variant A wins for low-PP postcodes.
Value deliveredData-informed creative generated in hours, not weeks. Predicted sales impact before any spend.
- 06
Activation — same day
Media IQ launches: CTV value messaging to households in 127 postcodes (frequency cap 5x over six weeks); DOOH variant C on screens within 1km of target supermarkets; hyperlocal bidding with higher bids in postcodes with the steepest decline; €180K budget paced over six weeks.
Value deliveredCampaign live within days of threat detection — not months.
- 07
In-flight optimisation — continuous
Week 2: "Erfurt postcodes responding 40% above average. Leipzig underperforming — creative fatigue at 4.8x frequency. Recommend creative refresh." Week 3: AI Analytics detects the competitor extending their promotion to Saxony. Brand Brain recommends expanding the campaign to 34 additional Saxony postcodes before consolidation.
Value deliveredContinuous optimisation informed by retail sales and brand health, not just engagement metrics.
- 08
Closed-loop measurement — post-campaign
Clean-room attribution matches exposure to retailer transactions: 11% incremental sales lift in exposed postcodes vs. matched control; 23% new-to-brand among exposed buyers; +1.1 share points regained; ROAS 5.1x (brand) / 4.2x (category) / 3.8x (product); exposed buyers purchased 1.4x more frequently; brand halo +6% on adjacent SKUs; value-for-money perception recovered +3 points.
Value deliveredComplete proof — not impressions delivered, but products sold, new shoppers acquired and share regained. The report the CMO presents to the board.
Benchmark ranges.
Drawn from the platform's capabilities. Use as projections, not guarantees.
- Time from threat to response
- Days, not months
- Incremental sales lift in targeted postcodes
- 8–15%
- New-to-brand conversion
- 15–25%
- Share points regained
- 0.8–1.5 pts
- ROAS (product level)
- 3.0–5.0x
- Cost per incremental unit
- €1.50–2.50
The question, the bridge, the proof.
“When was the last time you lost share in a region and didn't know why until the next quarterly report? How much did that delay cost you?”
“What if you could detect the threat in the first week, diagnose the cause in 30 seconds, and have a campaign live in the same week — targeting the exact shoppers your competitor is winning?”
“We match ad exposure to actual retailer purchase transactions. The report doesn't show impressions — it shows incremental units sold, new-to-brand shoppers converted, and ROAS validated at the product level.”
Keep reading.
Launching a new product into the right postcodes — not the entire country.
A €2M, 12-week launch for a premium organic SKU. Find the postcodes with the right combination of category growth, purchasing power, distribution and weak competition — and concentrate the budget there.
Proving advertising ROI to the CFO — in finance language.
Replace impression decks with reports the CFO actually reads: incremental units sold, cost per unit, ROAS at the product level — validated by matching exposure to retailer transactions.
Optimising trade promotion spend — store by store.
€12M of trade promotions across 30,000 stores, where 40–60% is wasted on stores already dominated or below the demand threshold. Score every store, match the right promo to each, and amplify with hyperlocal media.
Winning back lapsed shoppers — segmented by why they lapsed.
340,000 loyalty-identified shoppers haven't purchased in 90 days. Each represents €45 a year. Segment by lapse reason, run three parallel campaigns, and recover real revenue measured against retailer transactions.