From the original matching algorithms to show similar products to the sophisticated machine learning technology that now harnesses user behavior insights, the world of recommendations has changed immensely.

Over the years, online shoppers have gotten more and more used to seeing and acting upon product recommendations.

Indeed, according to Metail, 56% of consumers say they would be more inclined to use a retailer if it offered a personalised experience.

While we know product recommendations are a definite driver of ecommerce success, how exactly do they influence buyer behavior? Let’s take a look.

Definite influencer of purchase decisions

An Infosys study on consumer behavior showed that 59% of shoppers who have experienced personalization in their shopping agree that it affects their buying behavior.

In the real world, this impact on buying behavior could range from influencing a future purchase, to prompting an immediate additional purchase or even recommending a product to friends based on exposure to these recommended products on e-commerce sites.

One would think that features like product recommendations on an ecommerce site would only be truly appreciated by loyal, repeat customers who are exposed to the recommendation engine repeatedly.

However, the data above reveals that the impact of product recommendations is not limited to just brand loyal customers (it does work better on them, though).

More than one in six shoppers who were not loyal to a particular ecommerce brand acted on product recommendations and made a purchase.

Trigger impulse purchases

The same Infosys study discovered that 90% of surveyed online shoppers admit to impulse buying every now and then.

Source

The data above is extracted from a study which shows that only about 77% of shoppers indulged in impulse buys in 2008. This growth from 77% to 90% is a reflection of the increasing penetration of product cross sells and consumers’ growing response to the same.

Multiple studies support the fundamental principle of suggesting products to customers based on their preferences and user profile.

Often termed as a tool that ‘reduces the cost of thinking’ for the customer, product recommendations straddle that golden balance between keeping the customer hooked and the retailer profitable.

Incremental sales from product recommendations

Many ecommerce sites avoid offering too many product recommendations to shoppers to avoid losing on the existing sale as the customer gets distracted by the variety of items in front of them.

Popular conversion optimization wisdom says that distracting an engaged online shopper with other items is a trap that leads to abandoned shopping carts.

However, a study by the eTailing Group found that rather than acting as a distraction, product recommendations also result in incremental purchases.

A whopping 77% of online shoppers admit to have made additional purchases based on personalized product recommendations.

Even if they did not buy, over half of them browse through the recommendations offered to them thus increasing brand exposure and the probability of a future purchase.

Consumers display deeper drand loyalty towards sites with recommendations

It’s not just online retailers and brands that are keen on offering product recommendations to their shoppers. Over a third (31%) of respondents from the Infosys study actually wished for more personalized shopping experiences. The flipside is equally true.

At least 74% of online shoppers studied by JanRain apparently get frustrated with sites that show them content that has nothing to do with their preferences or past buying behavior.

Product discovery is an important component of the online shopping experience. Customers warm to a site that offers them personalized and handpicked recommendations over one that doesn’t. Almost all (96%) shoppers interviewed expected online retailers to inform them of exciting, new products.

Source

Product recommendations and millennials

One reason for the ready acceptance of online product recommendations has been the timing of their appearance. Product recommendations started being adopted across e-commerce sites around the same time as the Millennial generation began coming of age.

Research shows that this generation, born between 1979 and 1993, are born 'recommendation machines.'

With their high tendency to speak up on social media and other digital platforms about their brand experiences, 59% of Millennials admit to making product recommendations to others.

They even have a huge influence on purchase decisions beyond their own cliques. Older folk depend on recommendations from Millennials, as 74% of Millennials report frequently recommending new products to their parents.

Millennial Moms are an especially powerful demographic as influencers. Research from Weber Shandwick shows that 55% of Millennial Moms get asked for product recommendations and they tend to ‘like’ products on social media at least 10.4 times per month – a huge step up from older, non-Millennial Moms.

Automating product recommendations

In a scenario like this, product recommendation tools become an asset that not just aid an immediate purchase, they also help building customer loyalty, bringing customers back for repeat purchases.

'Customers who bought this item also bought…' isn’t limited to Amazon now. The ability to capture and interpret big data has made product recommendations more precise and tailored to every customer’s needs.

Recommendation tools now have the ability to auto-optimize delivery by showing the best performing product variations in real time to the appropriate segments.

In closing

Product recommendations come in many shapes and sizes.

From a shop assistant informing you about a great new product that’s hit the shelves in a real store to an online customer care agent offering an add-on product to the one you’re purchasing already, to even the on-site product recommendations that offer meaningful and well-researched upsells and cross-sells to existing customers, the possibilities are endless.

The advent of social media has only spurred this phenomenon of product recommendations and made it into something a lot more accessible to both users and brands.

The good news is we now have the technology for taking insights from website big data, social media and implementing a product recommendation project on your site. The even better news? Only 29% of marketers actually successfully implemented personalized recommendations on their websites.

This means you still have a fighting chance to beat the remaining 71% of websites who are struggling with this critical ecommerce element.

Pratik Dholakiya

Published 8 December, 2014 by Pratik Dholakiya

Pratik Dholakiya is Lead SEO & VP of Marketing at E2M Solutions and a contributor Econsultancy. 

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Comments (3)

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Nir Ben dor, Co founder at Barilliance

Great points Pratik, You may be interested in this recent Best practices study we've released recently about Product recommendations:
http://www.barilliance.com/product-recommendations-best-practices/

over 2 years ago

Pratik Dholakiya

Pratik Dholakiya, Lead SEO & VP of Marketing at E2M Solutions

Hey Nir, thanks for sharing the study. I'll have a look at it.

over 2 years ago

Bjarke Rosenbeck

Bjarke Rosenbeck, Marketing manager at relagento.com

Thank you for a interessting blogpost. I find it very interessting that 74% gets frustrated when pressented with "recomendations" that does not fit their prefferences. That makes sense and also it asks for the recomendation engines to be nothing but relevant in their recomendations.

over 2 years ago

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