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Worth a recommendation

Use the latest technology to assess customer buying habits and recommend items they might actually want

By using the latest recommendation technology, retailers and fashion brands can now choose to show their customers other products that they think shoppers may be interested in.

Not only does this help to increase the time shoppers spend surfing your site, it tempts them and helps to drive higher average spend. Better still, the technology provides shoppers with a useful service by assessing their buying habits and recommending items that they actually might want.

One company that has designed a version of recommendation technology is Peerius.

The science behind Peerius’ recommendation technology is simple: the software records the behaviour of the user, such as where they go on site, what they click on and what they buy, and uses that data to recommend other products.

In more complex examples, size, fabric, finish and style can also be taken into account. Finally, it records what recommendations have been successfully clicked on and bought and uses all of this information to build an even more accurate shopper profile for future transactions.

Peerius states that its clients can “start the process by inserting a single line of javascript into the html of their web pages”. From then, the data collection begins immediately.

Avail Intelligence also supplies a form of recommendation technology but it works slightly differently.

Once the technology is implemented, the process is entirely automated. It works by recording the behaviour of a user and then comparing it to the behaviour of other users. Companies can also chose to make manual recommendations alongside these, which is a a useful way to push slower selling product lines.

If the pattern of one user is similar to another, it then recommends products that the other user has viewed or bought.

In order to filter this slightly, etailers can also choose to add rules to the program so that certain chosen products do not appear in the recommendation tool.

Although fashion retailers are beginning to become aware of this technology, many are not using it to its full potential at present, or at all. Instead, they are creating a manual version of it.

The written explanation of how the retailer has selected which products to recommend must also be chosen carefully. For instance, while uses “Customers who bought this also purchased…”,, an online lingerie boutique, uses “Related products” and independent retailer Donna Ida has a “Stylist suggestions” section.

None of the above take into account the user’s own tastes or historical buying habits and therefore these etailers are blindly selecting products to recommend without the help of science.

Online retailing should be engaging and interactive. What better way to do this than to suggest to shoppers something they might actually want?

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