Changing the way we think about content in the customer journey
Search technology in ecommerce has barely evolved over the last decade. Just compare the intuitive experience and relevant results you get from Google, to the ‘Search not found’ result you often get when using the search bar when you’re shopping online.
If you’re one of the 50% of search users (i) who are lucky enough to find what you want when you shop online , chances are you’ve had to browse through a few pages of options first.
Last week, RichRelevance unveiled their new personalised search product, which has the ability to transform the search experience of online shoppers, and bring them faster and more relevant results.
This is likely to bring significant benefits to the shopper and the retailer, and for us content planners, it changes the way we need to think about content in the context of the customer journey.
How does personalised search work?
The shopper’s experience of Find (RR’s product name) is this. Once they start to type in a search term, they will be presented with auto fill options, as in Google, so they can either select from the options presented, or continue keying in their own term until the right one comes up. This search functionality is already in use by some retailers, but with Find, the key difference is this; as soon as you click on the search bar, an overlay comes in over the page and starts surfacing the products that you are searching for in real-time.
So, if you are searching ‘Jeans’ you immediately see the jeans, if you continue to add to that term, e.g. adding in ‘skinny’, the products you see will shift to match your new search.
Behind this, sits machine learning capability that identifies your customers and continues to build a rich profile about their shopping behaviours and preferences, which in turn enhances the relevance of their continued search results.
New content opportunities with personalised search
Firstly, Find changes the product experience. The shopper sees the right product faster.
Secondly, and most interesting from my point of view, Find’s technology enables the retailer to serve different content types at the point of search results.
The capability is there to present our shopper who is searching for skinny jeans, with a style guide and relevant social content at the same time as she sees the product options.
This provides the shopper with a richer content experience, that could enhance the brand experience and provide differentiation against competitors. This could form part of a strategy to address the real concern about lack of brand engagement in online shopping.
Bringing content into the customer journey
The content that is created to support the brand proposition in the digital environment, and to increase the desirability and kudos of product ranges, tends to sit outside of the natural customer journey.
The above chart tracks the type and location of content across desktop, mobile and app, for a UK based fashion retailer, for their Jean’s category.
We already know most traffic comes in via PLP and PDP. Content is generally planned into a one-way model of traffic that flows from homepage to PDP, and this reduces the shoppers’ opportunities to see (OTS) content, and limits our ability to learn about the real value of this content in the purchase process.
When we consider the mobile and the app experience, we see even less content built into the infrastructure. As the shopping journey gets even more streamlined for mobile, the experience degrades through the lack of content.
The main content components in these channels are text headers and cut out images. Efficient, yes, but lacking in differentiation and brand engagement.
Personalised search brings with it the opportunity to re-think the content and commerce experience.
How Personalised search will change our approach to content creation
Next week, I’ll cover the impact that personalised search capability has on retail content strategy, which looks at the following:
- Content access
- Product attribution and meta-data
- Customer insights
- Content performance
Thanks for reading. Let me know your views on personalised search
For more information about Find, contact RichRelevance Personalised Search
(i) Source: Independent research by Professor Michael Hendron