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3 Crucial Missions of Product Recommendation Tools in E-Commerce

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In this week’s guest blog post, we welcome Murat Soysal of Segmentify.com. Murat will go through 3 major missions of product recommendation tools in e-commerce and will guide you through how they act as the sales assistants of today’s shopping experience.

 

Disruptive is a fancy word in today’s ecosystem, but we should keep learning from best practices of our ancestors. This is a valid statement for ecommerce as well, which still has to learn so much from brick and mortar. The most crucial best practice that we still miss in ecommerce world is the “sales assistant” in physical stores. They know the old customers and they have the chance to get familiar with the new comers. Similarly, they are always well educated and guided about the products so they have the chance to guide the visitors during their conversion journey. Once defined like this, a sales assistant would be quite handy in ecommerce, wouldn’t she/he?

Product recommendation tools are the e-sales assistants, who help us providing the right offer to the right person at the right time and optimise conversion rates. These tools continuously observe our customers, learn their needs and select the most appropriate product for them. This includes three main activities.

 

1 – Get Familiar with Your Products and Customers

This is actually the first activity expected from a sales manager: Learn what we sell, how we sell and to whom we sell. This is really a complex process and needs time for an assistant to learn them all. On the other hand, when this is left to a machine in the e-commerce side, the product recommendation tools starts to learn both the products side and the customer side.

A sales assistant has the chance to observe a customer when they enter the store, talk to them to aggregate more information about them and behave accordingly.

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To benefit from this best practice in ecommerce world, product recommendation algorithms use all available data such as the source our customers is coming from (Direct, Organic or Paid), the location information gathered from IP address, the device type (mobile, Desktop or Tablet), the time they visit the site and etc in the first row. In addition, every single activity of a customer on our site such as viewing a product, investigating product descriptions and etc. These parameters are quite beneficial especially for getting familiar with the anonymous visitors.

 

2 – Personalised Service

Any piece of information is enough for a sales assistant to start a personalised conversation and generate a baseline to start a journey for the customers. And once the assistant aggregates enough information, the communication with the customer becomes more personalised based on the current needs and expectations of the customer.

In the ecommerce side, once the product recommendation is in use, the overall ecommerce experience provided to every single customer can be personalised.

This personalisation uses every possible opportunity to recommend products based on the behavioural analytics underlying. Customised home-pages “Selections”, categories “Trending Products” lists, “You May Also Like” widgets in product detail pages are the most common examples of the personalisation. The main idea behind using these widgets is to increase customer engagement, enable them to spend more time on our site and view more products. Although we have not mentioned conversion yet, research on customer engagement in ecommerce shows that a 5% increase in engagement could result in 95% in revenue. Now this should sound interesting.

Again to highlight, some best practices that should be copied from sales assistant actions are impressive when we personalise “search result” pages and “product not found” pages.

A successful sales assistant never only says “sorry we do not have what you are looking for”? and they always add “but look we have these ones you might get interested” or “our customers who are looking for that product actually buys this one since this is much more better”.

But you can see lots of ecommerce “empty search page results” which in practice says “You can leave now, I can not sell any products to you” which definitely kills the conversion rates.

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As a friendly advice, personalised product recommendations in an “empty search page results” results in a minimum of 15% CTR.

Similarly, the fancy “not found pages” are much more better than “404” pages but again personalisation of these nice fancy pages with selected products would keep our customers on site.

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3 – Keep Tracking

And the final step in the way of a successful sales assistant is to learn continuously, based on your current and previous conversations with the customers. How they respond to your questions, and alternative product offers are the key findings of an assistant that might be the most valuable opportunity in converting the visitor.

Definitely, this is a built-in function of product recommendation tools with using the positive and negative feedback which is in other words learning from feedback of your customers to your product recommendations.


Surely, while you get to know your customers better, and offer them the personalised experience that they’d enjoy, you should still be keeping in mind that: your customers are price-sensitive too!

They know who sells at what price pretty well, so you should also put yourself in their shoes, and gain the same market knowledge before they do.

Prisync can help you track online competitor price automatically and help you to set the right prices that will convert your visitors into repeat customers.

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NOTE: You can now share your voice in our blog. Prisync Blog now accepts guest blog posts and you can see the guidelines here. If you are already writing on ecommerce, or thinking of it, just reach us out!