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Sales Intelligence – Critical calculation, data consistency, competitor matching, AI visibility & German localization issues that should be fixed early

Hi EMR team, I have now tested Sales Intelligence very extensively across the Self-Service Prospect Report, Full Analysis and Battle Plan, including several different businesses and the German/DACH customer-facing experience. First: the concept and design are genuinely strong. Sales Intelligence could become one of the most valuable features in EMR for agencies because it connects prospecting, diagnosis and sales in one flow. However, I have found a number of issues that I believe are important to address while the feature is still relatively new. Some are clear calculation or data-logic bugs. Others are wording, methodology and localization issues that make modeled or estimated data sound like verified business outcomes. This matters especially in a white-label environment: the prospect does not know these claims come from EMR. They believe they come from our agency. If a prospect notices one obviously incorrect calculation, trust in the entire report and therefore in the agency can disappear immediately. I have already sent Support a detailed report and screenshots. I am posting everything here as well because I think these issues are important enough to solve early, before more agencies build their acquisition process around Sales Intelligence. Environment Product: Sales Intelligence Areas tested: Self-Service Prospect Report, Full Analysis, Battle Plan Customer-facing language: German Market: Switzerland / DACH White-label agency use case 1. Battle Plan review target calculation is mathematically incorrect One tested business has: Current rating: 4.2★ Current review count: 398 Target shown: 4.5★ Battle Plan says: “2 Bewertungen benötigt” / “2 reviews needed” It also generates: “At 4.2 stars, just a few reviews away from 4.5 display threshold.” This cannot be mathematically correct. If the true average were exactly 4.20 and every future review were 5 stars: (4.20 × 398 + 5 × n) / (398 + n) ≥ 4.50 approximately 120 additional 5-star reviews would be required to reach a true 4.50 average. I understand Google may expose only a rounded rating. If EMR does not know the exact underlying average/rating distribution, then an exact number such as “2 reviews needed” should probably not be shown. Expected result: Calculate the requirement from valid underlying data and clearly state the assumption, or show an estimate/range instead. Example: “Based on the current review volume, sustained positive review growth is required to move toward 4.5★.” This is one of the most important bugs because agencies may quote this number directly during a sales conversation. 2. Equal monthly review velocity is incorrectly marked as a deficit Full Analysis shows: Prospect: 0 reviews/month Leader: 0 reviews/month Yet the prospect receives: “RÜCKSTAND” / “BEHIND” and: “0 frische Bewertungen monatlich mehr benötigt zum Aufholen.” 0 vs. 0 is equal, not behind. Expected logic: Prospect < benchmark → behind Prospect = benchmark → neutral/equal Prospect > benchmark → ahead 3. Competitor/entity matching appears incorrect In one Full Analysis for UM bio restaurant, the system selected “Europa” as the market-leading competitor and average Google Ma

Gean Occhiuzzi about 21 hours ago

💡 Feature Request