Search and
Product Reviews: Best practices for improving conversion rates

Why read this eBook?

When thinking about what compels shoppers to buy, modern ecommerce businesses must consider the value consumers are attributing to product reviews. Reviews are no longer just a part of modern life — looking up a restaurant on Yelp or researching a new toothpaste or a book to read — but a key element in the buyer’s journey.

Scott Cook, co-founder of Intuit and director of eBay and Procter & Gamble, famously said: “A brand is no longer what we tell the consumer it is — it’s what consumers tell each other it is.” Data from Forbes is here to support this:

• 49% of consumers trust reviews as they would 
recommendations from friends or family 

• 75.5% of consumers put their trust in online reviews when making a purchase decision

• 89% of consumers read reviews before purchasing a product, with more than half reading at least 6 reviews before purchase

• 21% of consumers claim reviews help introduce them to local businesses

Data from a 2020 study by Trustpilot

There’s also a direct correlation between reviews and sales conversion: products with 50 Reviews have a 30% sales lift, Furthermore, for every $1 of online revenue, another $6.50 of in-store revenue is influenced by reviews. This eBook outlines how to best utilize product reviews to boost conversions.

 

Product reviews: Search technology and best practices 

Best practice 1: Search & filter within reviews

A search bar in the review section may seem obvious but it is in fact quite powerful. When visitors come to the destination page, they can be overwhelmed with a large amount of content. A search box placed in a prominent area gives users one more tool to help easily and quickly navigate to the answers they’re looking for.

This is much like what we are seeing on a TripAdvisor page.

Search technology best practices

By the time a user arrives at the search page, they usually already have a good idea of what they’re looking for. Let’s say that, before booking this hotel, they care a lot about the quality of the WiFi connection. How would they get a sense of how good WiFi is? Of course, the hotel may say that they have excellent WiFi, but what is the actual experience of guests who have stayed here?

There are over 1700+ reviews for this hotel. The visitor clearly cannot read them all, but they can use the search to sift through all reviews and find ones that mention WiFi. When they hit “enter” they learn from the rating summary that the general sentiment is very positive, but that there are some reviews that mention issues with WiFi. Now they have a more complete picture, and can decide how it influences their decision to book this hotel or not.

Furthermore, TripAdvisor’s UI allows users to drill down to reviews relevant to their situation — filtering, for example, on traveler type and time of the year. In addition, TripAdvisor creates a guided search experience by letting users filter on commonly used phrases in reviews. For instance, by looking at the review section in this hotel, users immediately learn that there are popular discussions around the milky way and a breakfast buffet.

Filtering allows a deeper level of precision to tailor content to what users want. It essentially takes a large haystack, makes it a more manageable haystack, then makes it easy for people to find the needle.

Best practice 2: Rich content snippets

To form a positive impression on users once they arrive on site, sites can incorporate a snippet of a review along with the product results. Rich content snippets can mean a 20-30% increase in click through rates.

Here is an example of a Yelp search result page that takes advantage of content snippets:

Let’s say that our shopper performs her search for “foundation for oily skin” on Ulta, a beauty chain and online store. They will get back a set of results, but will have no idea how these products are related to oily skin:

The UX is not helping her understand why products are relevant to her search query.

What if, by contrast, our shopper could see, interspersed with relevant search results, a piece of content on the topic of her searched item?

They could immediately drill down to product results with endorsements relevant to oily skin, and see why results are relevant to her purchasing criteria—without having to click through all the products and without researching each individual product page. This is very much in line with consumer expectations set by Google search: when we search for something on Google, we see rich content snippets that make it easy to understand why results show up.

Note that the user here is not searching just products but also reviews that match the query. Influenster chose to show reviews over generic marketing copy, layering an aspect of trust and transparency early on in the discovery process for the shoppers. This a win for the retailer not only because 92% of consumers say they trust reviews over branded content, but because there are limitations in relying on branded content as searchable text. 

More and more, users are searching for solution-oriented expressions, such as “wedding day foundation” or “best strollers for jogging.” A product description would rarely contain such expressions, whereas product reviews do. Thanks to Google, natural language searches have become a norm in search behavior which site search technologies must be able to match.

Best practice 3: Different types of content

When thinking about all the ways a shopper may want to consume knowledge during the exploration or identification, retailers should consider offering search results beyond plain text. Videos and images are more engaging, lifestyle-oriented possibilities to offer consumers in the course of the discovery process. There are also related discussions they can explore with crowdsourced answers, lists other users have created relevant to their query, and last but not least — if they’re looking for something more curated—articles from the retailer’s platform.

The modern user experience is all about empowering users to find what they need, rather than making assumptions for them. The search technology UI should provide the ability to leverage real estate on the screen to showcase different content types and allows users to switch contexts seamlessly, as well as the ability to index all these different content types, configure their rankings differently, and search all of them simultaneously.

Best practice 4: Sorting & ranking within reviews

Amazon doesn’t use a simple ranking strategy to sort the reviews. Amazon users can filter reviews by verified purchase, as well as the format of the comment (e.g., whether it contains an image or video). Users can also sort reviews by rating and recency. On top of those features, Amazon displays comments ranked by age of comment, helpfulness votes by customers and whether it is a verified purchase or not.

On the product detail page, Amazon has a product review summary section which displays a “Customer Reviews” graph showing star ratings broken down by percentage. In addition to being able to filter reviews by the number of stars, users can see the top positive and top critical reviews.

Another important factor: what Influenster calls a user credibility score. It incorporates things like whether the user uploaded a profile photo — ensuring there is a real person behind this content — as well as whether other members on the platform are flagging or liking their content. With over a million reviews every month, it’s helpful to have this type of a self-teaching model based on how other users voted the value of that person’s content.

Consumers have, in fact, gotten more sophisticated with product reviews. They take reviews with a grain of salt, depending on who wrote it and how the review is written. If several reviews on Yelp are written in a similar tone or by people with little history on reviewing restaurants, consumers will sense that something is off.

Companies like Trustpilot and TripAdvisor have teams solely dedicated to monitoring content and removing spam.

One of the ways for ecommerce sites to tackle this is to hone in on the review ranking method so that they are showcasing their best content. The other way is to work on spam detection algorithms. This is a key area of investment for modern brands who often have one chance to make a good impression and build trust, especially with consumers coming to a site for the first time.

 

Product reviews: Looking ahead

Let’s take a look at what’s coming up and what more we can do to better engage users in the customer journey with product reviews.

Thinking mobile

In 2012, U.S. consumers spent $7.8 billion in retail purchases on their smartphones. By 2016, this figure had grown to $60.2 billion. Forrester anticipated it would reach $93.5 billion in 2018 and $175.4 billion in 2022. According to Gauss, they spent $491.1 billion in 2023. Even though people are still using computers to shop, browsing and researching is definitely happening more on mobile.  

In short, mobile optimization is a crucial area to focus on. This means focusing on faster experiences, easier searching through features like voice search and personalization, and looking beyond long-form text content and into more digestible forms like short form video.  

Personalization

Companies that have incorporated personalization have seen their revenues grow 2 to 3 times faster than those that still use a wholesale, generic approach.  A hot topic overall, personalization in ecommerce also means displaying reviews that are relevant to your users.  

In this example from Rent the Runway, the company has tagged each review user’s profile with their height, age and body type. Once the user is logged in, Rent the Runway can use search technology to boost reviews that came from users with similar body types. This makes it easy for reviews to resonate with shoppers and accelerate their purchasing decision. 

Similarly, Influenster plans to release a feature where consumers can see what characteristics they share with other reviewers — say a skin concern or a dietary preference. They will also  be able to filter reviews from users who share their attributes. 

Video content

As screens have gotten smaller and attention spans have gotten shorter, consumers want more digestible content that is still rich and informative. Short form video is a format we see dominating here, especially as the younger generation is getting trained in content consumption through platforms like Instagram and Snapchat. Think about the experience of seeing a lifestyle blogger running in the perfect pair of leggings in an Instagram post versus reading reviews about the material. Video reviews allow you to fully capture the atmosphere and experience of a product or place better than you could with photos or text alone.

We are just now at a point where videos are becoming searchable through accessible audio transcripts that can be pushed to search technology indices. By opening up this content for search, ecommerce sites can access natural language searches that are more authentic and mirror the syntax people use for search.

Voice search

A 2019 study found that 62% of regular voice-activated speaker users were likely to buy something through their device in the next month.

In fact, 43% of shoppers used smart speakers to shop in 2020. That number will certainly increase as natural language processing becomes more sophisticated in the search sphere.  

Voice search is very well positioned to search within reviews. Voice queries tend to be  wordier and more long-tail, capturing consumer intent and natural language searches to  maximize conversion possibilities. 

 

Product reviews and the buyer’s journey

Businesses are able to convert users because they’ve understood the consumer’s intention and what it ultimately takes for shoppers to make up their mind. Product reviews clearly matter, but how do they map to the customer’s journey from the moment users begin discovery to the point of purchase?

Consumption state

When consumers turn to their phone or computer for information on something they want to purchase, their behavior generally falls into one of three consumption states: exploration, identification, or transaction.

• Exploration
  Is this product right for me?
  “when should I get life insurance?”
  “travel ideas for families”
• Identification
  What kind of product/service is right for me?
  “best sunscreen for oily skin”
  “best headphones for runners”
• Transaction
  Where do I buy this?
  “buy coconut oil online”
  “Converse of white”

In the exploration state, the shopper is exploring if a product is right for them or how it fits into their life. They’re not sure about this decision and are trying to confirm it. Here, they’re asking exploratory questions like “when should I get life insurance” or “travel ideas for families.”

Next, in the identification state, the shopper is looking to identify the right type of product for them. They’re sure about the product they want but they’re researching appropriate options specifically for them. Here they’re searching with queries like “best sunscreen for oily skin” or “best headphones for runners.”

The last consumption stage is the transaction phase where the shopper is sure about their need and wants to buy the product right now. Here they’re trying to answer questions like who and where to purchase from.

In all three consumption states, search and discovery have a key role in meeting users where they are in their shopping journey. In other words, exploration, identification and transaction states all show different search intentions.

The buyer’s journey

Let’s walk through an example of what a buyer’s journey through these consumption states might look like. A shopper starts by exploring skincare products for wrinkles. By searching on their favorite skincare website, they immediately learn about a list of products that fix their problem: anti-wrinkle creams, eye creams, moisturizers.

Next, they’ll move to the identification state where they have identified the specific product they want to buy, let’s say a moisturizer. They will then find out which moisturizer is best for their skin type.

Once they decide on the moisturizer they want to purchase, they can go to the product page and evaluate different shopping options, which completes the transaction state.

We can see how a seamless search experience is one of the key aspects of accelerating the conversion process during any of the consumption states we’ve described.

Now, let’s look at how search experience can help utilize product reviews — AKA user-generated content — to motivate conversions in the course of the buyer’s journey. We’ll analyze best practices used by ecommerce leaders, and talk about the future of product reviews which have become a de facto key component in the modern ecommerce era.

 

Conclusion

If content is king, then user-generated content is queen, charged with capturing user intent and behavior for quicker conversion wins.

Search is more than query and results — it’s a conversation your users have with your product. Search should be an ongoing conversation rather than a one-and-done experience. And, when it’s done right, the consumer must feel understood by the engine.

Businesses that can incorporate search within reviews and apply filtering, ranking, and sorting on reviews will accelerate the shopper’s purchasing journey because of the social proof and layer of trust it adds.

Learn more at www.algolia.com