This is the 4th issue of our InfluencedRevenueIndex series, where every month we’re reporting the success metrics for our personalisation for ecommerce technology, PersonalMerchant.
To recap August’s metrics, we began looking at the performance of PersonalMerchant based on the number of items sold, and saw an average of overall influence of 32.3%.
It’s important to remember that the InfluencedRevenueIndex looks at all of our online retail customers, for the month 1-30th September. New customers went live with PersonalMerchant at differing times throughout the month, and we have noticed a two-week period between go-live and noticable improvements on revenue.
September has seen a slight increase in the influence on sales, growing by 5%. We’ve also seen a reduction in the clicks-to-buy distance, showing that PersonalMerchant is helping to put the right products in front of the right people, faster.
Influence on sales
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We can see that for the fourth month, there has been an increase of influenced sales generated by PersonalMerchant, however directly influenced sales have fallen. This can be attributed to the number of new clients who went live in September, where not enough behavioural data has been collected to supercharge relationship-driven algorithms in use.
Direct influence on sales: 11.84% of sales were directly generated by PersonalMerchant. We call this a “shotgun” purchase, where the visitor is suggested a product, clicks on it, adds to basket and checks out immediately.
Indirect influence on sales: Indirect influence on sales for September was 21.03%. These are sales where we have suggested the item in the same session as it is purchased.
Total influence: An average of 32.87% of sales were influenced or generated through PersonalMerchant.
Influence on buy distance
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PersonalMerchant also tracks the number of clicks it takes a visitor to complete a purchase. A lower buy distance indicates the visitor found what they were looking for quickly, and part of PersonalMerchant’s remit is to try to reduce the buy distance by suggesting the right products in front of the right visitor, quicker. Our click-to-buy distance includes all clicks to pages viewed before the transaction in that session – this includes blog pages, homepage, category and product page views, as well as checkout process clicks (where we tracking them).
We can see the beginings of a steady trend of lower click to buy distances, having dropped from cicks to buy distance fell from 23 in July to 18.5 in August. This also fits with a reduction in the average number of unique page views per visitor, which fell from 1.97 in July to 1.94 in September.
Interested in finding out how we can improve your revenue and lower click distance with personalisation?
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