Product Recommendation Strategies Based on Your Audience Segments

product recommendation strategies based on audience segments

Effective product recommendations can yield massive results in terms of conversions. Did you know, more than 35% of Amazon’s purchases are attributed to personalized product recommendations!

Of course you do, we’ve told you that before.

In fact, according to a study by Accenture, 75% of customers are more likely to buy from retailers that offer product recommendations.

And another survey from Accenture showed a whopping 91% of customers are more likely to shop with a brand that offers recommendations relevant to them. Product recommendations keep the visitor hooked, increasing the average time spent on a website, and hence, increasing the chances of a sale.

Moreover, visitors get a chance to explore products that they didn’t know they needed. This report shows 49% of customers purchased a product from a personalized product recommendation, that they didn’t plan on buying.

Product recommendations offer promising results if done right. And to do it right, you need to have a strategy in place! Through this blog we will explore a few strategies to get product recommendations just right for your eCommerce website.

But with a twist – Product recommendation strategies based on your audience segments.

Quick recap of product recommendation strategies

Product recommendations work only when they are relevant to your visitor. If the product recommendations resonate with the visitor, it will straight away drive them to a successful purchase. However, if the recommendation is irrelevant, it will make no difference whatsoever.

In that context, making a successful product recommendation involves a few key factors. These are: the strategy itself, the audience, the webpage the visitor is on, and the timing of it all.

The strategy itself requires considering a lot of factors as well. It is not one thing that makes a good product recommendation strategy, after all, there are many ways to recommend products to anyone. Be it their purchase history, browsing history or similar products.

Here are a few product recommendation categories:

  1. Similar Products: similar products can be recommended in two different contexts. Firstly, let’s say a customer is already on a product page, then products similar to that specific product can make a good recommendation. The other is when the customer searches for something specific but your store does not have that exact product. So within that search result similar products can be recommended to the customer.
  2. Personalized: this is a more complex way of recommending products, and it has a higher impact. It involves looking at the audience or the visitor and the products to find an overlap. Many factors such as past purchases, view history etc can be taken into account to offer personalized product recommendation.
  3. Bought Together: Simply put, if the functioning of one product is supported by the other, you recommend it. For example, if the product the visitor is looking at is a battery operated fan, then the product recommendation can be batteries.
  4. User History: this category involves the visitors preferences, browsing and purchase behavior to recommend them similar products.
  5. Recently Viewed: One of the simplest recommendations, a list of products the customer has just viewed.
  6. Recently Purchased: This a list of products that are being purchased by other customers in real time.
  7. Last Purchased: These are the previous purchases of the customer.
  8. Similar to Recently Viewed: These are the products similar to the ones recently viewed by the customer.
  9. Most Popular: These are the most frequently bought products in the store. Further, these can be categorized further like Most Popular in the Category or Most Popular in a City. Depending upon the nature of your store, you can use variations of the Most Popular products.

The above are a few basic categories for product recommendations. Any of these can be used solely to make up a product recommendation strategy.

However, a combination of these, known as a hybrid strategy, works best. For different pages on your website, different product recommendation categories may work best.

To learn more about how these different categories of recommendations translate to a strategy, read this article: Types of Personalized Product Recommendations To Increase Sales.

Similarly, for a particular set of audience, a specific category might work best.

In that context, we will explore product recommendation strategies with two contexts: first, the webpage they are placed on, and second, the audience that they cater to.

Product Recommendation Strategies by Audience Segments

Product recommendations only work if they are relevant to the viewer. In order to bring forth the best and most effective product recommendations, you need to be thoroughly aware of the audience you are catering to. There is no one size fits all when it comes to product recommendations. Each product recommendation can be personalized to give optimized results.

As noticed previously, categories of product recommendations are quite limited when it comes to first time visitors. And in the case of first time shoppers or visitors, you can’t really offer much personalization to begin with. On the contrary, for returning customers you can use a plethora of categories to give them the best product recommendations.

Now, to cater to both these groups, you need an intelligent product recommendation engine in place that can recognize, assess and deploy the subsequent strategy. This would depend on the data available, the context, the user behaviour, previous history, view history and much more factors.

For example, viewers for which the data availability or information is low will generally be recommended products using categories like “Most Popular” or “Recently Purchased”. These categories don’t require any information on the viewer. However, recurring shoppers, returning customers would offer more data in terms of past purchases, view history, cart history, and therefore categories like “Personalized”, “User History”, etc. can be used.

So according to the user profile the product recommendation strategies vary. Let’s look at a comprehensive list of audiences and the possible strategies for them.

First Time Viewer

First time viewers know very little about your store, and similarly you know very little about them. This offers you a clean slate to put your best foot forward and recommend all your bestsellers. However, it also restricts you initially, since you can’t give the first time viewer personalized recommendations. So for this set of audience, the strategy revolves around a hybrid combination of “Most Popular”, “Most Popular in the Category”, “Recently Purchased”.

You can also step it up and leverage the little information you know about the first time viewer. Suppose they have stepped into your store from a Google search, then the context of the search can be utilized to show them products. For example, if they were searching for a black sweater, then you can push the bestsellers from that category.

For this you can also leverage the “Similar Products” category. Similarly, the viewer could have landed on your store from an ad. In such a case, you can show them products featured on the ad. Once a first time viewer clicks on any product, now you have enough information to push forth similar product recommendations and employ other strategies.

Seasonal Shopper

A seasonal shopper is one who occasionally shops at your store. For this set of audience, you have a lot of data already at hand to work with. From their previous purchases, to their viewing history and even things they once wishlisted or added to their carts. Leveraging all this information you can truly offer them personalized product recommendations. This strategy would be a hybrid combination of “Personalized”, “User History”, “Last Purchased”, “Recently Viewed”.

For this set of audience, you can also push product recommendations via email and ad campaigns. This can be clubbed with other email campaigns and offers you have running. This customer type is familiar with your website, so you can skip bestsellers and recently sold products, instead show them products relevant to them.

Loyal Customer

This is a set of audience that has been consistently shopping with you. And for a loyal shopper you have almost a complete profile of what they like and dislike. Here you can make personalized recommendations that should directly yield a profit. Loyal customers tend to restock whatever they bought from you last, in such a case “Last Purchase” is one category that becomes crucial. This makes it easier for the customer to straight away purchase their favorite products.

Further, for this set of audience, personalized recommendations can be made via email and other communications channels. This is a set of customers that looks forward to what you have to sell, so ensure you give them the best recommendations. Here a combination of “Personalized”, “Last Purchased”, “Recently Viewed” works well.

For all of the above sets of audiences, micro segmentation of product recommendations can be done. This could be based on the gender, age, requirements etc. of that specific customer.

Additionally you can set up merchandising rules for audiences based on the nature of the product you are selling. For example, you can push discounted or clearance products to low-value customers, and refrain from doing the same with high value customers.

Now that you know how to target different audience segments with product recommendations, let’s quickly go over how you can add a layer of page-context on top of this strategy.

Product Recommendation Strategy by Page Context

Different web pages or sections of an eCommerce website can benefit from product recommendations. Product listing pages, category pages, cart pages, and even homepages can host product recommendations.

In some cases, you can even use overlays and popup recommendations. For each of these you can pick and choose a category or a combination of categories to ultimately maximize potential revenue.

Let’s look at a few different webpages on a generic eCommerce store, and the product recommendation categories that work best for them.

Homepage

The homepage is a clean slate, and gives you a lot of room to experiment. Most categories work here for regular visitors. Such as “Last Purchased”, “User History”, “Personalized” etc. But for new visitors, the product recommendations can be only “Most Popular” and “Recently Purchased”. Regular or returning visitors can be recommended products based on the existing information, like their view, purchase and cart history.

Product recommendations on the homepage allow you to guide the user to the product directly. And for new customers, it helps you put your best foot forward with your most popular purchases.

Category Pages

These are product category pages, and the “Most Popular in the Category” product recommendation is a good fit for this. Along with this “Personalized” product recommendations can be made if the user is a returning user.

Category pages don’t offer much scope other than the popular and personalized categories. However, you can also add a “Last Purchased in this Category” list, which is nothing but the products purchased by customers from that specific category.

Product Detail Pages or PDPs

Product detail pages are one of the key pages for product recommendations. Here, many different categories can be used to make up a hybrid strategy. One of the most easy and basic categories that works here is “Similar Products”. And the other that is good for maximizing profits is “Bought Together”.

Especially if one of the products is dependent on the other for functioning or use, “Bought Together” product recommendations work best. Product detail pages are on their own very influential in terms of the impact they have on the customer. A well designed, optimized product detail page has a direct impact on the sale. And further, an optimized product recommendation here can drive up the average order value or AOV. Apart from “Bought Together” and “Similar Products”, other categories like “Personalized” and “Last Viewed” also work well here.

You can choose whatever works best for your store, and for the type of products you are selling. Since, PDPs play an important role in the buyer’s decision phase to complete the purchase, make sure you put a category that will add to the profit whilst giving the buyer a nudge to complete the purchase.

Checkout Page

Checkout page is a very crucial page in terms of the sales cycle of an eCommerce store. Here, the customer is about to either abandon or complete the purchase. Similar to the PDPs, the product recommendations that work here should not only add to the average order value or AOV but also nudge the customer to complete the purchase. This is the time to make any upsells, which means almost all categories of product recommendations work here.

The best fits being, “Bought Together”, “Similar Products” and “Personalized”. If, for your store, products are generally bought together, then that is the category you should go for. If not, then the other two work best. However, a combination will also work to push the customer to complete the purchase with an add on.

This can also be supported with an additional discount for opting a product recommendation. For example, if the customer was about to purchase an item X, and they also opt for an add on item Y then they get 10% off or free shipping.

Product recommendations strategies can be broken down page by page, but it is not limited to that.

In fact, by using widgets powered by AI-powered recommendation engines like Wiser you can place a recommendation virtually everywhere on your website.

Depending on your product, you can create and test different layouts and placements across your eCommerce store to find the best fit for product recommendations.

You can even opt for a standalone recommendation page, that offers curious viewers a catalogue of interesting and relevant products. Further, product recommendations can also be made by using exit intent popups, theme based landing pages, via email campaigns, etc.

Product recommendation strategies are subject to various factors. There is no one sure shot way of many great product recommendation strategies. Experiment with hybrid strategies and A/B test different types of recommendations to assess your customers. Once you get a hang of what your visitors like to interact with the most then you can work towards establishing that strategy.

With an easy to use app like WISER you can test different widgets and compare different product recommendation strategies to find out what works best for your eCommerce store.

WISER offers AI based personalized recommendations across your webstore, mobile and email to drive upto 35% higher conversions.

Get your free trial today!

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