The author suggests that retailers focus on three key metrics: item count, average order value, and conversion rate. The article also highlights the need for retailers to move away from broad, one-size-fits-all discounting and instead adopt a more streamlined approach that prioritizes personalized targeting and tracks ROI to ensure profitability. This approach is particularly relevant given the current market conditions, where affordability is a major concern for consumers and retail margins are tightening.
Key takeaways:
- Despite the phasing out of third-party cookies, 80% of marketers still rely on them for their marketing activities. This highlights the need for a shift towards using first-party data for personalized interventions.
- Propensity-based targeting, which uses AI and machine learning to predict customer behavior and serve personalized interventions, is a promising application for first-party data.
- Online retailers can focus on three key metrics in the context of propensity: item count, average order value, and conversion rate. These metrics can help retailers manage inventory, increase the value of their existing audience, and improve conversion rates.
- With the tightening of retail margins and the need for more efficient promotions, propensity-based targeting can help retailers rightsize their promotions and ensure profitability.