It feels like there are new technologies coming onto the scene every day: AI, geolocation, mobile marketing, VR, AR, social media… the list goes on. With so many tools available, it’s no wonder seemingly ‘mundane’ customer reviews get left behind. But it doesn’t have to be this way.
You can apply some of these new technologies to your customer reviews in order to unlock their previously hidden potential. By combining data processing with customer reviews, you will be armed with a powerful weapon that you can use to achieve exceptionally high levels of customer experience and satisfaction. It’s time to look at customer reviews from a new angle…
Unlocking the benefits of NLP
Let’s start with the most tech focused opportunity, using natural language processing (NLP) to enable machine learning analysis of your mountains of review text. That might sound a bit daunting at first, so let’s break it down.
Natural language processing (NLP) is the technology that allows digital assistants like Siri to understand you. It’s also heavily employed by Google to decipher searches made using natural language rather than keywords. This ability for a computer to understand the meaning, and intent, behind natural human text is what makes the next step possible.
Machine learning powers big data analysis. Put plainly, this technology allows you to analyse datasets that are far too large for humans to handle, and then return various insights you can use to improve your marketing. These insights can vary from understanding which types of advertising are most effective with which demographics, to specific customer preferences. And with accurate knowledge of customer preferences, another AI system can then create personalised marketing campaigns tailored to them.
When we combine NLP and data analysis, we unlock all sorts of large new datasets. You can now collect all the general chatter about your company on the web and analyse it to gain insights<. This isn’t just some keyword analysis that counts the number of positive or negative words associated with your business. The computer will literally understand the intended meaning behind each of the thousands of sentences it reads, and then return actionable insights.
Your review data makes a prime target for NLP analysis. It’s written in natural language, and it’s full of customer opinions. One subtype of NLP analysis that is particularly relevant to review data is sentiment analysis. Sentiment analysis lets your company understand what is being said about your brand/product, as well as how users feel about it, on a massive scale. The insight this method provides will allow you to increase customer retention and engagement, which will then improve your average customer lifetime value.
Now that you have a newfound appreciation for the versatility of your review data, let’s talk about some of the things we can do with it that don’t require complicated machine learning solutions…
Reviews are a powerful tool for building social credibility. For modern consumers, reading the opinions of their peers is a key part of the purchasing process. We know that marketing messages will always say a product is great, but a reviewer is putting their genuine opinion out into the world with no agenda.
Interestingly, bad reviews may not be so…bad.
Even a review with a less-than-perfect score can positively impact a customers decision to make a purchase more than any marketing can. Because the value of reviews comes from their genuine nature, it’s important to keep your reviews “natural”. It can be tempting to remove some negative reviews, or incentivise positive ones, but this is a bad idea. Seeing some negative reviews actually adds credibility to the positive ones and can further increase your sales.
Use reviews for SEO purposes
An honest review section also works wonders for your website’s SEO. Each review adds to the total amount of relevant, and unique, content about each product on your site. This will add to your perceived authority and relevance in the eyes of a search engine.
But it’s not just on-site reviews that boost your SEO, a large number of reviews on third party sites can help even more. This is because Google’s algorithms detect a large amount of content discussing your products, or business as a whole, and raise your status accordingly. The more positive reviews you have, the greater the positive impact on your SEO.
Reviews and social proof are also proven conversion rate improvers, so include them prominently on product pages.
Incorporate reviews into your marketing strategy
We have talked about how reviews can influence your customers, now let’s talk about effective ways you can integrate reviews into your marketing to start seeing those benefits. Simply adding one or two customer reviews to the end of any product-specific marketing is a good place to start, but it’s 2018 and we have the technology to do better.
he effects of social proof on your customer will be amplified by seeing reviews from people similar to them. So why not use AI to match reviews to the customer individually? The best type of data to match will depend on your business, but matching age and socioeconomic status is a safe start. Teenagers will care more about what other teenagers think, and successful businessmen will care more about what other successful businessmen think, no surprises there.
A bonus side effect of this approach, is that because AI is selecting which review to show, it won’t show the same ones to everyone all the time. It may even select a review with slightly incorrect grammar. While that would discourage a marketer from including it in a widespread campaign, on an individual level its fine, and it adds credibility.
So there you have it — whether you decide to focus on using NLP techniques to turn your customer reviews into new datasets, leverage the social proof factor of reviews, or use review marketing to boost your sales — reviews are central to good business. Make sure that you encourage your customer community to share honest and detailed reviews, and don’t panic if you do get a bit of bad press. Address the issue, acknowledge the failing, learn from it, and move on.