NEW YORK: Retailers should worry less about abandoned digital shopping carts and focus more on gleaning usable consumer information from such visits and combining it with other metrics, according to a new report.
Noting that over recent years online shoppers have consistently failed to check out around two thirds of the time, insights provider eMarketer said that this was not about the effectiveness of e-commerce platforms so much as how consumers used carts.
It suggested three main reasons for high abandonment rates, including ingrained consumer behaviour, the growth of mobile shopping and a slow economic recovery.
eMarketer went on to argue that "abandonment rates are not terribly meaningful by themselves, but they can be quite meaningful when viewed in conjunction with other metrics and in the context of shopper intent and buying cycles".
Simply putting an item in a cart immediately highlighted what a shopper might be interested in buying, even if they didn't actually do so on that occasion. But instead of just using this data for remarketing purposes, retailers could be achieving more by combining this data with other metrics.
Web analytics typically focused on individual sessions when what was really required, said eMarketer, was a visitor-centric approach that included offline data.
For example, customers often visited a site many times before making a purchase, becoming more likely to buy with every visit. Retailers needed to link up this behaviour with in-store purchases, loyalty card data and email addresses. But there remained, eMarketer conceded, an issue with attribution.
Basic attribution has become increasingly challenging with the spread of available channels and many marketers are settling for using last-touch metrics.
Writing in Admap, Peter Cain of Marketscience Consulting, proposed an econometric modelling approach to this problem which would allow marketers to understand how various media combinations impacted on consumers.
The proposed framework informed business planning in four key areas: traditional and digital ROI, marketing budget allocation, media laydown, and simulation and forecasting.
Noting that over recent years online shoppers have consistently failed to check out around two thirds of the time, insights provider eMarketer said that this was not about the effectiveness of e-commerce platforms so much as how consumers used carts.
It suggested three main reasons for high abandonment rates, including ingrained consumer behaviour, the growth of mobile shopping and a slow economic recovery.
eMarketer went on to argue that "abandonment rates are not terribly meaningful by themselves, but they can be quite meaningful when viewed in conjunction with other metrics and in the context of shopper intent and buying cycles".
Simply putting an item in a cart immediately highlighted what a shopper might be interested in buying, even if they didn't actually do so on that occasion. But instead of just using this data for remarketing purposes, retailers could be achieving more by combining this data with other metrics.
Web analytics typically focused on individual sessions when what was really required, said eMarketer, was a visitor-centric approach that included offline data.
For example, customers often visited a site many times before making a purchase, becoming more likely to buy with every visit. Retailers needed to link up this behaviour with in-store purchases, loyalty card data and email addresses. But there remained, eMarketer conceded, an issue with attribution.
Basic attribution has become increasingly challenging with the spread of available channels and many marketers are settling for using last-touch metrics.
Writing in Admap, Peter Cain of Marketscience Consulting, proposed an econometric modelling approach to this problem which would allow marketers to understand how various media combinations impacted on consumers.
The proposed framework informed business planning in four key areas: traditional and digital ROI, marketing budget allocation, media laydown, and simulation and forecasting.
Data sourced from eMarketer; additional content by Warc staff
