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How To Personalize Ecommerce Site For Four Types of Customer ?


According to the Realities of Personalisation report in 2013, we found that 98% of respondents saw personalisation as critical to success. But the latest Conversion Rate Optimisation report by Econsultancy and RedEye shown that just only 22% of respondents said they had implemented website personalisation, a small number.

Infrastructure and cost are the main reasons that the companies explain for this lag. Although website personalisation is very difficult (36% viewed it as very difficult to implement in Econsultancy 2015 CRO study) but we should still do that.

Simon Peirson from Barilliance gave us a few ideas; he spoke at the Festival of Marketing about personalize Ecommerce site for four main types of customer. Here are his tactics.

1/ How to personalise for the “Just-Browsers”?

The habits of “Just-Browsers” users: 

  • Frequent visits.
  • Browses a “New products” category.
  • Browses multiple categories.
  • Sorts by “New arrivals” if possible.

Some suggestions to personalise for “Just-Browsers” users:

  • Personalise new arrivals based on category/product browsing history.
  • Personalise suggestions based on real-time environmental data. Example: track the user’s location, if it’s raining, then display certain products if appropriate.
  • Send email newsletters which included personalised product recommendations to known customers.
  • Send browse-abandonment email and adding discount codes where appropriate.
  • Engage anonymous visitors to enter their email address. It’s a good way to incentivize users to sign up to a newsletter.

2/ How to personalise for the “Researchers”?

The habits of “Researchers” users:  

  • Arrives from external search and lands on product/category pages.
  • Browses within a single category.
  • Sorts by reviews if possible.

Some suggestions to personalise for “Researchers” users:

  • Paid-search message reinforcement allows product recommendations on a category page to be aligned with the incoming search term (at a more granular level than the category displayed).
  • Add live sales counters to product pages.
  • Use social proof within these product recommendations served to referrals from non-branded search.
  • Match sizing in suggestions, where appropriate (e.g. shoes or baby clothes). For example, when a customer selects a size seven, remove shoes from suggestions that are out of stock in this size.

3/ How to personalise for the “Price Sensitives”?

The “Price Sensitives” users often:

  • Uses “sale” keywords in search terms.
  • Arrives from a shopping comparison engine.
  • Visits sale categories or clicks on promotion banners.
  • Sorts products by price, from low to high.

Some suggestions to personalise for “Price Sensitives” users:

  • Personalise recommendations based on search term, showing sale items to those that arrive from Google with a sale-relevant query.
  • Track mouse movement to gauge likelihood of imminent abandonment and use this to offer coupon/discount messaging relevant to cart contents.
  • Displaying the cheaper products when users choose to sort products from low to high.
  • In some business sectors, customers can incline to copy product titles and use them to shop around (e.g. electronics); you can display a price match guarantee when users highlight a product name.

4/ How to personalise for the “Ready-to-Buys”? 

“Ready-to-Buys” users are the people:

  • Arrived from a cart abandonment email.
  • Have added items to the shopping cart.
  • Have started checkout.

Some suggestions to personalise for “Ready-to-Buys” users:

  • Adding coupon codes automatically when they clicks to buy from cart abandonment email.
  • Create urgency by using countdown timer in checkout page, time left to use coupon codes.
  • Create urgency by show stock numbers left.
  • Create the urgencies, displaying number of other shoppers who viewing the same product, agoda.com is an example.
  • Displaying number of people who have bookmarked to creates urgency and validation.

Source @econsultancy.com

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