1. Increase Your Sales With Product Recommendations Include
2. Increase Your Sales With Product Recommendations For A
3. Increase Your Sales With Product Recommendations Samples
4. Increase Your Sales With Product Recommendations Examples

We already know how important recommendations are for all of us, no matter what we are talking about: products, services, people, places, beauty, health, animals.

This fits perfect to ecommerce businesses and they already know that, especially the first example we give you: Amazon, because it seems like more than 60% of it it’s devoted to recommendations.

Online shops use these because they know it could help them gain customers, increase revenue, improve conversion rate and boost the average order value.

Equipping your team with the right skills to increase sales productivity should be as great of a focus as providing them with the right tools. Effective onboarding can reduce ramp-up time by 30 – 40%, and continuous training can lead to a 50% increase in net sales per rep. 14 Sales Strategies to Increase Sales and Revenue 1) People Buy Benefits People don’t buy products, they buy the results that product will give. Start your process of identifying your ideal customer by making a list of all of the benefits that your customer will enjoy by using your product or service.

Today we will talk about recommendations from two different perspectives: for those who already bought something from your website and for those who aren’t your clients yet, for different reasons.

1. They already bought something

In this case the recommendations are based on the purchase habits of a group of customers and you may see them with messages like: “you might like”, “your friends liked” and “other people who bought this also bought”.

The recommendation engine observes your visitors’ shopping behavior, for example pages and products they visit, what they are searching for, what they add to cart or their previous purchased products and they link this behavior to past decisions of other people with the same profile .

Ecommerce sites found different messages to integrate recommendations in their website:

– www.junarose.com – Wear this with

This clothing website, JunaRose is giving you some recommendations for the same products but different models, so you can choose which one fits better to your taste.

– www.asos.com – You might also like

The well known asos uses models to present its products, so the customers can see how those products may look on a real person. Asos variates its recommendations: sometimes they use products from the same category – if you choose a skirt, then in the suggestion area you will see only skirts, or they combine them – if you choose a dress, then they will show you a nice pair of sandals.

– www.hm.com – Style with

H&M has two different types of recommendations: if you choose to shop a product from the main list you will see the window below with a small message: Style with.

But, if you will go on your favorite product’s page and then add it to your bag, you will receive two types of messages at the bottom of the page: Style with and Other also bought.

– www.bensherman.com – We recommend

BenSherman.com has the same strategy as JunaRose and they show to their visitors only products from the same category. They are not trying to convince you to complete your look by giving other products.

– www.burton.com – Questioner – Your Results

Now this is a special one. Burton.com recommends you some products based on your answers. They give you a questioner and at the end of it you will receive Your results. That’s funny because, they are not guessing, they go for sure!

Some pretty simple questions to find out more about what you want and then you have… Your results!

– www.amazon.com

And now world’s first example when it comes to recommendations: Amazon. They try to sell more, in different ways, with different messages – text and position, all on the same page!

– Frequently bought with

– Your Recently Viewed Items and Featured Recommendations

– Customers who Bought Items in Your Recent History Also Bought:

2. First visit on your website

Increase Your Sales With Product Recommendations Include

In this case you have two possibilities to present your recommendations:

• show them most purchased products on your website:

• identify the product with the highest chance of acquisition.

The more options you give them, the more undecided they become. But you have to try to turn this kind of visitors into an opportunity: turn a lost order into a placed order.

Find out what your visitor’s favorite product is and then make him a special offer, for his special product. He will not only buy that product, but he will also start loving your business.

By doing this, you’ll give him a little incentive and you have all the chances to turn that visitor into a customer because you can convince him with this live product recommender. Happy memorial day!.

You can find out what they want based on their browse behavior by using a marketing automation software.

Now that you find out about all these possibilities you have, start to create your own message for your products recommendation.

Stop loosing money! Gain customers and increase your revenues!

Do you have any product recommendation on your website? Great! Share with us your success!

Here is another secret we want to share with you: Why your product page isn’t selling…

Sources:

Product recommendations can multiply profits.

Unfortunately, many eCommerce companies install a simple plugin and leave it at that. The truth is.. not all recommendations are the same.

We've found that detailed, personal recommendations vastly outperform generic ones. To be successful, you need sophisticated product recommendation engines that are able to make sense of shopper's web behavior.
Select below to see how personalized product recommendations work, statistics on how effective they are, or best practices when implementing your own personalized content strategy.

Note: this page was updated on September 7th, 2020 to reflect the latest findings on product recommendations, content personalization, and their effect on eCommerce sales.

Personalized, predictive product recommendations: examples & how they work

We covered in detail how advanced product recommendation engines work here.
However, in brief, I like how Amazon details how their recommendation engine works. 1.2 limits analyticallyap calculus 14th edition.

Barilliance helps eCommerce store's create predictive, effective product recommendations with machine learning and AI capabilities.
Here is how it works.

Personalization depends on customer data.
Barilliance incorporates three major sources of data to create personalized product recommendations.
They are:

1.Aggregated data (category/product views, adding to cart and purchase data, internal search queries, etc.)
2.User specific data that is used to personalize the recommendations. Similar to aggregated data, user data is the specific user interactions such as which categories and products the user viewed, bought, etc.
3.Static product data that is supplied by the client in the product feed. Product feed data typically includes price, availability, brand, tags, and other product attributes.

To create effect personal product recommendations, Barilliance uses a variety of machine learning optimized algorithms.
Our AI technology selects which algorithm to use to fill the product recommendation widget based on who the user is and in what context they are viewing your site.
To illustrate, take the home page experience.
The visitor could either be a new visitor or a returning visitor.
If the user hasn't visited the site before, than a series of best selling products will be displayed.
However, if the visitor is returning, visitors will see personalized recommendations based on their previous engagement with your brand such as:

- Products related to their recently purchased items
- Products related to their recently viewed products
- Top sellers from their recently viewed categories

Finally, you have the ability to define merchandizing rules for any number of demographic or behavioral segmentations.

We covered merchandizing rules in our article [Guide] Advanced Product Recommendation Tactics to 3x Revenue.
From there, we shared how:
'the best engines allow retailers to 'overrule' the software's recommendations in lieu of explicit merchandizing rules you set up.
Examples include:

• Restrict recommendations to only show full priced items
  
• Avoid brand conflicts on particular product pages
  
• Prioritize transitioning season items
  
• Prevent low in stock items from being shown

Create Personalized Product Recommendations with Ease: Create compelling offers and increase AOV with Barilliance's AI and machine learning powered recommendation engine. Request a demo here.

Personalized product recommendation statistics: conversion rates and more

To demonstrate how effective personalized product recommendations are, we've gathered data on how recommendation widgets impact eCommerce stores across the customer journey.

Below we look at statistics for: average order value, revenue, conversion rates, and shopping cart abandonment rates.

Personalized product recommendations dramatically increase AOV (average order value).

Sessions that do not have any engagement with recommendations have an AOV of $44.41.

This number multiplies by 369% when prospects engage with a single recommendation. The effect continues to climb until tapering off around 5 clicks.

It is clear that the more personalized and engaging recommendations are, the more stores benefit from larger purchase orders.

*Note: This study went across multiple industries. The significance of this study is not the nominal amount, but the relative increase.

We conducted a study across 300 randomly selected customers. Here's what we found.

Increase Your Sales With Product Recommendations For A

Product recommendations account for up to 31% of eCommerce site revenues.

On average, customers saw 12% of their sales attributed to our product recommendation product.

“Product recommendations account for up to 31% of eCommerce revenues. On average, customers saw 12% of their sales attributed to our product recommendation product” - Barilliance Research

We also found that product recommendations increase conversion rates.

Above, we see the conversion rate of sessions increase in lock-step with their engagement.

Increase Your Sales With Product Recommendations Samples

Again, the biggest improvement occurs at the first click. Prospects who do not engage with recommendations convert at 1.02%. That number increases 288% after a single interaction.

Our findings fell in line with a similar study conducted by SalesForce. They found shoppers that clicked on recommendations are 4.5x more likely to add items to cart, and 4.5x more likely to complete their purchase.

Lastly, recommendations have a significant effect on shopping cart abandonment.

Here, we defined cart abandonment as sessions that completed a purchase divided by the total sessions that prospects added an item to their cart. We then segmented these numbers by how they engaged with recommendations in that session.

We found that sessions that did not engage at all with recommendations, but simply added an item to their cart were much more likely to abandon their purchase.

In fact, implementing personalized product recommendations can improve cart abandonment by up to 4.35%.

Lastly, it is interesting to note that the effect on cart abandonment reverses after a certain level of engagement. This makes sense when you consider buyer behavior - especially those in the research phrase that use recommendations to find products.

Tips for Effective Personalized Product Recommendations

Position of product recommendations influence how effective they are. We found widgets placed above the fold were almost twice as effective (1.7x) as widgets below the fold.

Out of the 20+ product recommendations types that were reviewed in this study, the most engaging recommendation type was ‘what customers ultimately buy’.

When a new visitor comes to your store, you don't know what products to recommend.

Increase Your Sales With Product Recommendations Examples

The best practice is to supply the best sellers of your store toward the top. You can also consider having multiple widgets, one for each of your top categories.

As customers engage with your site, your product recommendation engine will begin to understand what types of products this customer is interested in, and supply more personalized suggestions.

Position of product recommendations influence how effective they are. We found widgets placed above the fold were almost twice as effective (1.7x) as widgets below the fold.

This falls in line with our findings ondynamic content that increases conversion rate.

Another great way to personalize emails is via product injections. Software like Barilliance can inject product recommendations directly into the email.

The widget is tailored to reflect the products each customer is most interested in. Below is a great example of tailoring suggestions based on gender.

Below is an infographic we built with some of the key product recommendation stats we found.

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Next Steps..

Product recommendations serve as the foundation for your eCommerce personalization strategy.

The next step to increase conversions is to build out more advanced personalization tactics.

• Retention Strategies - Improving retention by just 5% can lift eCommerce profitability by 55% - discover the highest performing retention strategies here.
• eCommerce Conversion Optimization Guide - Discover how to increase conversions through a variety of tactics here.

Lastly, to see if Barilliance is the right product recommendation engine for you, schedule a brief demo with us.