In the competitive world of retail home goods and appliances, half the battle is simply knowing who is actually ready to buy. For years, independent retailers have relied on broad audience segments, essentially casting a wide net and hoping for the best.
But as this retail marketing group discovered, "hoping" leads to wasted ad spend and missed opportunities. By shifting from generic targeting to propensity-based modeling, they didn’t just improve their numbers—they revolutionized how they support their network of independent retailers.
Here is how they turned data into a 120% lift in conversion rates.
The Challenge: The High Cost of "Broad" Targeting
This retail marketing group supports a massive network of independent retailers, each with unique shoppers and buying cycles. The problem? Their marketing teams lacked a reliable way to identify which consumers were effectively "in-market."
Campaigns relied on:
- Broad Segments: Targeting everyone rather than the right one.
- Generic Messaging: Lacking the nuance needed to close a sale.
- Wasted Spend: Paying for impressions on people who weren't ready to purchase.
They needed a smarter, predictive way to focus their budget on the audiences most likely to convert.
The Solution: Propensity-Based Audience Modeling
This retail marketing group partnered with Further to implement Compass, a marketing intelligence platform that consolidates data and powers AI-driven activations. This wasn't just about gathering data; it was about scoring it.
Demographics told part of the story. Intent told the rest. By unifying media, behavioral, and performance signals like conversion rate, CPC, and CTR, Compass enabled the retail marketing group to target propensity—not profiles.
This approach allowed them to:
- Identify High-Intent Shoppers: Pinpoint exactly who is most likely to purchase.
- Prioritize Audiences: Shift budget away from low-intent browsers to high-intent buyers.
- Tailor Messaging: Deliver the right message at the exact moment of decision.
The Results: Efficiency Meets Growth
The shift from broad targeting to precision activation delivered immediate, measurable impact across key retail categories. By focusing dollars on shoppers with the highest likelihood to buy, this retail marketing group achieved:
- 120% Lift in Conversion Rates: The most significant indicator that they were finally reaching the right people.
- 24% Increase in Traffic: Proving that precision doesn't always mean lower volume.
- 13% Reduction in CPC: Lower costs combined with higher performance.
Key Takeaways
Data Quality is Gold: Clean, unified data is the difference between experimenting with AI and actually activating it.
Stop Chasing Demographics: Age and gender don't buy refrigerators; intent does.
Score What Matters: Not all clicks are created equal.
Let Behavior Lead Budget:Shift spend in real time to where shoppers are ready to buy.
Activate intent. Optimize faster. Win at retail. Contact us at info@gofurther.com
