This blog was written by the Founder and CEO of Localyser, Tarik Qahawish

I have worked with hundreds of local businesses and multi-location brands over the past five years to help them take control of their online reputation using our tool. In the process, we have seen several strategies that if implemented correctly can have a huge impact on store sales.

I’m of course referring to how restaurants, auto showrooms, hospitals and gyms can use a hidden weapon called online reviews. It really comes down to three things:

1. Learning from online reviews to improve operations.

2. Responding to all reviews on a consistent manner.

3. Generating positive reviews organically but with a little help.

Let me dive into each strategy one by one.

Analyzing Reviews

Before digging into this one, I must preface by saying that to derive actionable insight from online review you need to have a large enough data set to make it reliable. If you have one restaurant location for example and you are only getting a handful of reviews a week this won’t work that well. However, if you have more than ten locations for the same food concept, then you’ll have enough data that could be statistically significant.

It's also worth mentioning that you must have access to all your review sources from across the Web to have a complete picture of what each customer segment is telling you. Yes, Google can sometimes be the dominant source of your online reviews but if you have a decent delivery orders then you must also look into the reviews coming from delivery or aggregator apps such as Deliveroo, UberEats and Zomato. Moreover, in some countries such as Canada you also have local review sites that the locals use more often (e.g., RestoMontreal which is popular in the province of Quebec).

Another pre-requisite to consider is to also have an easy way to collect these reviews preferably through an automation tool like Localyser but it can also be done manually (lots of copying and pasting through). This is important because you need a searchable database to dig deeper with some keywords (e.g., service or name of a dish) as well as a good visual reporting to track KPIs such as average star rating over a date range such as the past 30 days, breakdown of positive versus negative reviews and a chart of where reviews are coming from (their sources from the Web).

Now that you have all of this set up, what I would recommend is to incorporate the insights from online reviews into your weekly or monthly operations meetings. I have been invited to several of those and found that having access to your online review reporting during these meeting can be quite helpful. This is because most operational manager don’t have access to reliable customer feedback data and in its place are observations and past experiences which can produce false positive decisions.

Here are the areas I would look at during these operations meetings:

• Month over month (MoM) star rating increases or decreases across all locations broken down by source (e.g., Google, Zomato).

• Number of reviews changes MoM and the percentage of negative reviews.

• Response rate and time to respond changes MoM for all locations (this should be at least 75% for the response rate with a 2-day maximum to for response time).

Localyser has a ranking report that breaks all of these KPIs and automatically calculates the MoM changes for each location (see below our Ranking Report).

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You will quickly see two data point stand out, the top performing locations and the bottom performing stores. The former helps you identify what your best stores are doing right to learn from and apply them to all locations. The latter requires a deeper analysis to understand why they are struggling compared to the rest of your portfolio. Then go ahead and start reading the negative reviews for those low performing locations. You will quickly find trends in the review comments and identify at least one area that can be fixed quickly and assign someone to take care of it.

For the lucky brands that have so much review data that reading them one by one is time consuming, you can leverage some Excel word count tools to identify the most repeated words in the reviews. In our clients’ case, we have recently introduced an Insights report (see below) that uses machine learning and natural language processing to automatically categorizes reviews into pre-defined categories. For restaurant operators as an example, the categories are broken down as follows:

• Food related (taste, quality, quantity).

• Service related (speed, friendliness).

• Delivery related (speed, accuracy, packaging)

• Atmosphere related.

• Price / value related.

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Responding to Reviews

It goes without saying that responding to reviews not only helps win back unhappy clients but also converts future ones who are reading those negative reviews online. In fact, according to a recent study by Qualtrics, 82% of buyers are said to be influenced by how a brand responds to reviews.

But how do you make sure that your team is able to respond to 100% of the reviews in a timely manner without breaking the bank. The answer is automation! Otherwise, start by focusing on your most important source of reviews such as Google and slowly expand from there. However, you need the following pieces to be in place to achieve this high KPI levels:

1. First and foremost, make sure your team has access to all your listing accounts on Google, Facebook, Yelp, TripAdvisor, etc.

2. For Google, you’ll need to claim and verify your listing before being able to respond to reviews. The rest have an easier ownership verification process.

3. Prepare well written response templates.

4. Figure out who will be doing the response management, this can be centralized at the head office or decentralized at the store level.

Once you have everything set up and the team ready to go, I recommend making this task as part of their job role and establish performance objectives such as a minimum response rate and minimum response time. If you are just starting out, start with an achievable goal such as 50% response rate with a response time of 3 business days. Once the team reaches this objective this KPI, celebrate it and increase it to 75% then 100% with an ideal response time of 1 day.

This can definitely be done manually at first by logging in and out of each review site platform, but you’ll soon find out that as you grow in terms of sales and number of locations you will need to automate this process with a reliable online reputation management tool.

Generating Positive Reviews

I’ve saved the most important point until the end, but I cannot emphasis enough how important the first two above are as without them, generating reviews won’t be as affective. It’s kind of like hiding dirt under the carpet or not addressing the root cause of the problem. Generating more positive reviews can be a good short-term tactic to increase your star rating but Google relies on other signals to rank map listing on search queries; namely keywords, location proximity, response rate and time (brand engagement with your customers) among other things.

I would also add that generating more positive reviews should come in an organic and consistent way and not as a campaign blitz that you run once and a while. It is also preferable to ease your customers to leave you a review and not put them on the spot by having your staff ask customers straight up; “hey, can you leave us a review?”. This puts unwanted pressure on your staff and your customers; your staff will immediately have a bias to only ask happy customers for reviews and customers will feel uncomfortable to leave a review and might want something in return like an incentive (this is a big no no which I’ll cover at a later post).

The solution is to equip your team with a feedback tool instead that suggests to customer to share their comments online. You will not only make this process easier on both parties by digitizing the user experience (think of a QR Code that links to a short survey) but it also removes the pressure to leave a review on the spot. Asking for feedback (link to feedback blog post) is much easier to do and most customers are happier to provide it.

Conclusion

I have seen hundreds of our clients follow the above 3 prone strategy and have seen incredible results. It’s like having a snowball effect: the more your learn from existing reviews to fix operational issues the happier your customers will be; the more you respond to reviews the more you win back and retain customers and the more you generate reviews the higher your ratings on Google and other review sites will be.

This makes your online presence more discoverable and will increase your traffic to your store, website and ultimately increase your orders and sales in the form of table bookings, in-store visits, take out, etc.

And this is how you leverage online reviews to increase your store sales.