Online Product Reviews: Get to the entire customer story

As a savvy retail brand, the question you should be asking is: “Do we have the one source of consumer truth and are we listening to the entire consumer story?” The fact is, most consumer brands don’t because they are only relying on the data they see. This is because most brands are relying on the tried and true research methodologies to plan and optimize their marketing and product strategies.

This includes surveys, focus groups, and social listening data. To be fair, these are valuable data sources that do give indications of what’s going on in the market. However, any plan created without product reviews is incomplete. It’s an essential piece of the puzzle that is missing. If you’re not using this data type, you’re not truly listening to your consumers.

This blog will explore the different data sets being used for product reviews and why brands still don’t have the whole truth.

The Data You See: Surveys, Focus Groups & Product Reviews

Most brands and retailers feel confident that they’re empowered with the right data sets. As we said earlier, this includes surveys, focus groups, and social listening. These different data sets can inform some business decision-making with their insightful mix of quantitative and qualitative data. They can indeed give businesses a sense of consumer sentiment.

There are a couple of major issues when it comes to surveys and focus groups. They are both a drain on financial and time resources. Most importantly, there are inherent biases in both methodologies. Focus group participant responses can be influenced by the overall group dynamics. The battery of questions is about known topics, topics of interest, or the obvious.

For instance, if we were doing a survey about shampoo, some questions could be:

• Did you like the smell?
• Is it expensive?
• How did it make your hair feel?

However, in reality, there may be underlying issues impacting a brand or product that aren’t included in a survey or focus group. Take, for example, topics around the shampoo model, gifting, defects, ingredients, and formula, to name a few.

Keep in mind that surveys still remain the top methodology. According to Greenbook, “89% of market research suppliers and clients regularly use online surveys.” Oftentimes, it’s precisely the questions NOT covered in a survey and focus group and their responses that are truly the most important to understand.

The Other Data You See: Social Listening

The naysayers out there will say that’s what social listening is for. There’s no way around it–social media is a free for all, where users share their opinions with no holds barred. It also significantly shapes and influences public opinion on everything from politics, to of course, purchasing decisions. This TikTok video on the top shampoos in 2024 got over 4.7M views, plus thousands of likes and comments. It’s clear this influencer’s recommendations are driving consumer purchasing decisions.

By using a robust array of social media tools, retailers will likely succeed in collecting data about the number of post engagements, comments, and sentiment. This is also true of brands that create special campaigns with a targeted hashtag to track engagement. An added bonus is the identification of influencers who are later employed by the brands to boost sales even more.

There is most definitely a lot of buzz and opinions. But let’s face it, not everyone expressing an opinion on social media has purchased a product from your brand. So when your sophisticated platform calculates brand sentiment, it can’t be correlated to sales. Therefore, how much should you be depending on the sentiment based on social media for your business decisions? Not only that, but social media sentiment is very broad.

Businesses can’t drill down and learn the sentiment for a particular product SKU. They can’t even get sentiment around product attributes. Just think back to our earlier shampoo example and the number of attributes mentioned. That’s not even all of them!

The Data You Can’t See: Consumer Listening

As opposed to social media which focuses on general chatter on the various channels, consumer listening can be much  more targeted and essential. Why, you ask? It means you’re focusing on post-purchase data culled from online reviews. This is from the true voice of the consumer who is providing his/her honest opinion. It’s something to be taken seriously since only 5-10% of consumers take the time to write an online product review.

So if someone does take the time to write a product review, then businesses should sit up and listen. This is especially true if the review is organic, and the consumer didn’t receive a promotion to write it. 

Similar to social listening, a sentiment analysis can be performed on an online review. However, because this medium is so rich, business can access sentiment on a variety of levels:

• Category sentiment analysis: This refers to the sentiment analysis of an entire vertical whether it’s cosmetics, apparel, or appliances, the right tool should be able to provide that bench mark. Category data is important in providing insights into key players and the overall competitive landscape.
• Brand sentiment analysis: Strategic companies need to know what consumers think about them. Leverage the data to get a snapshot of how consumers feel about competitors.
  

• Product sentiment analysis: Because consumers leave reviews about specific products, businesses are empowered with sentiment data that showcases the ‘Why’ around their product’s success or failure. Plus, they have the ability to delve deeper into the competitors’ products.
  

• Topic sentiment sentiment: A single review can cover several facets of a product from overall satisfaction, price point, quality, and more. The topics vary based on the product context. Consider the thickness of toilet paper vs. the coverage of cosmetic foundation. Consumers talk about everything and the topic sentiment can help map product innovation.

AI for Accessing the Data You Don’t See

As we explained earlier, businesses are empowered with the data they have, but suffer from a severe blind spot—the data they don’t see. This conundrum is illustrated in this visual of the iceberg, demonstrating that most businesses are accessing 30% of the known data. To access the other 70%, brands need AI.

So what’s the secret ingredient to making it happen? Simply, generative AI. It’s the engine behind the scenes powering the calculations and performing sentiment analysis after sentiment analysis on just about every facet of a consumer review. Most importantly, the AI engine needs to have some understanding of the product context.

Beyond that, the AI is organizing the data in a cohesive manner so it can be interpreted consistently. Answers are ready in moments at the click of a button as opposed to months. It’s a major game-changer for consumer insights professionals.

Conclusion

In today’s competitive retail landscape, traditional data sources like surveys, focus groups, and social listening often leave brands with an incomplete understanding of their consumers. Consumer reviews provide a direct line to the true voice of the customer, offering nuanced, post-purchase insights that other methods miss.

By integrating this data into your analytics framework, you can bridge the gap between perceived and actual consumer experiences, empowering your brand to make informed decisions, enhance product development, and better meet customer expectations.

To truly understand your consumers, it’s essential to incorporate their product reviews into your strategy. Learn more about getting the full story based on your product reviews.

Florence Broder

Florence Broder is a marketing professional with over 20 years of experience. She has worked in a range of global high-tech companies.