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Analytics Merchandising Personalization Product Recommendations 

5 Ways an Online Recommendation Engine can Increase Sales

If you own an ecommerce site, it can be difficult for you to stay ahead of the competition, continue to innovate and offer an incredible shopping experience to your customers. So then, what is the best way for you to attract customers and increase sales on your ecommerce site?

While there are a multitude of factors that influence sales, I’m particularly going to talk about how product recommendations can help you increase online sales. Today, online shoppers value recommendations and expect ecommerce sites to personalize their shopping experience.

‘According to a Forrester study, 15% of the visitors admit to buying recommended products.’

Ecommerce sites should take into account visitor location, social context, browsing behaviour and other key signals to show context rich suggestions. In this post, I’ve highlighted 5 ways in which an online recommendation engine can increase sales dramatically using the power of a personalized recommendation engine.

Offer personalized shopping experience to your visitors

Personalization plays a crucial role in showing relevant products to visitors. It offers a compelling shopping experience leading to greater conversions.

‘According to a recent survey,74% of consumers get frustrated when the websites they visit feature content, offers, and ads that don’t match their interests.’

It’s necessary that your recommendation engine efficiently analyzes your visitor’s on site behaviour and understands their preferences.

Manual recommendations cannot deliver accurate recommendations to the extent an automated recommendation engine can. At the most, a manual recommendations engine can allow site owners or merchandizers to map categories to complementary categories or specify recommendations per product which will never be as accurate as the recommendations delivered by a personalized recommendations engine.

Automated systems on the other hand, can provide more relevant recommendations by tracking visitor interactions, current behaviour, location etc and analyzing their preferences.

 For example, Unbxd helps you show accurate recommendations to your visitors by analyzing how your visitors interact with your site in real time and understanding their product preferences. It uses personalized widgets such as ‘You may also like’, ‘Viewed also viewed’ and other widgets to show recommendations on key properties/pages of your site.

recommendations unbxd

Cross sell complementary products to your visitors

Large retailers like Amazon attribute almost as much as 35% of their conversions through product recommendations. Recommendation widgets like ‘Bought also bought’ show complementary products to visitors which enhance product discovery and boost conversions.

Here’s an example of Amazon showing related products such as sandals, handbag etc as recommendations for a dress.

amazon recommendations

Show recommendations that deliver Social Proof

According to a recent research, ‘Content sharing (reviews, testimonials etc.) can influence consumers more than price and brand, and motivate people to spend 9.5% more’.

Social proof is effective in today’s post-modern internet savvy generation as it relies more on what your peers have to say about a product and how they feel about it. Recommendation widgets like ‘People who viewed this also viewed’ show recommendations based on the wisdom of crowd and use social proof to engage visitors.

On a lighter note, Jeff Bezos once said, “When you have a bad experience offline, you tell 6 people, online you tell 100 people.”

Zappos, a popular online shoes and clothing shop, shows recommendations which foster social proof with this handbag.

WW

Personalization based on location & time 

We’ve already discussed how ecommerce sites analyze user behaviour and consider social proof to offer relevant recommendations. Now, some recommendation tools are also considering location/weather to go a step further in their personalization efforts. Location-based recommendations definitely make product suggestions more relevant and contribute to higher & faster conversions.

For example, during summers it makes sense to show recommendations for summer dresses. You would show different top sellers in Miami than the ones you show in Alaska primarily because of location/weather differences. Unbxd personalizes the top seller widget based on location so you can cater to visitors from different locations with the same widget.

Upsell alternate products to your visitors 

Suppose you’re selling mobiles on your store and a visitor is viewing a particular mobile, you can then showcase recommendations of high-end mobiles or cell phones with better features. This solves two critical purposes –

1. You are able to show more products and give better options to visitors which they may not have discovered otherwise.

 2. A high-end mobile phone with better features will be priced higher, hence encouraging visitors to spend more and will help increase the average order value across your site.

Recommendation widgets like ‘More like these’/ ‘Similar products’ are often used to upsell products. These widgets along with personalization can help increase conversions significantly.

Asos, an apparel and beauty store upsells with the ‘We recommend’ widget to show similar products.

asos upsell

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I’d love to hear what you think about these recommendation techniques and how have they helped you increase your online sales, do share it with me in the comments below.

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