Nestore's blog

Why measure in-store traffic?

Say Jamy, if customers come into the shop and buy, the turnover will be good. No need to do X.

Yes and no Fred. Sales are an important indicator of a store's success and long-term viability. But it's not enough to measure relative performance or to exploit a shop's potential.

Good sales figures can therefore be indicative of under-exploitation of potential (a low conversion rate, for example) as well as outperformance. So it's worth looking at a range of indicators.

Obviously, the more extensive a brand's network, the more complex the data collected will be in terms of providing insights and areas for improvement for each location. Conversely, brands that are expanding will need to be careful to focus on just a few indicators and on ways of improving their performance.

Measuring data - yes, but what, why and how?

There are several categories of data. At Nestore, we summarise them in 5 main categories:

• Raw data : Our concrete side!
• Qualifying data : Go blue!
• Behavioural data: Run off to your room.
• Personal data: Nestore, 7 years, 01 79 72 71 77
• Qualitative data: A weakness for chocolate?

Some of this data is based primarily on statistical models, others are the result of actual observations and finally some is the result of human intervention. Of course, the difficulty of capturing this data, the scalability of this approach and its cost vary according to the degree of precision chosen.

It is vital to ask what use is being made of the data collected. Faced with this huge task, brands have too often chosen the solution of collecting everything. They then store this data in a datalake: a big, deep, peaceful thing in which you don't fish for much, but which can quickly lead to drowning or an encounter with Nessie!

Once you've set your objectives, here's a non-exhaustive list of what you can collect at the point of sale.

1. Raw data

This data does not give any indication as to the specific nature of customers. This data is for statistical purposes only.

The most basic is point-of-sale traffic. This is measured either by GSM and WiFi technologies placed in the shop, or by agencies aggregating estimates from telephone operators (which is therefore never real-time data), or by GPS technology (via the integration of an SDK), but the accuracy of which remains highly debatable.

We can add the conversion rate (which can also be measured using infrared to count the number of people entering the shop), the frequency of revisits and the time spent in shop.

Finally, you need to think about the cashier data (average turnover, number of tickets), which completes this analysis.

The success of a drive-to-store campaign can be measured in terms of in-store traffic generation or turnover over this period.

We can also look at changes in brand awareness (social networks, share of voice, etc.) following the opening of a point of sale, a pop-up or the creation of a new concept.

2. Qualifying data

This is an initial qualification of the raw data, an initial segmentation.

Age groups, gender, social class, origin (tourists vs. locals) and range of products purchased. This data is much more complex and costly to obtain. GSM, Wifi and Bluetooth technologies can provide some of it, but if not, you need to use video, which can be used to segment customers and link this information to checkout data.

3. Behavioural data

To go one step further, we can look at customer behaviour. Video allows you to understand which products are calling and which are converting by looking at the customer's journey through the point of sale. This gives you access to a more detailed analysis of your conversion rate.

Video is also a very good tool for interpreting your bounce rate. On a website, this is calculated by dividing the number of visitors who have only visited one page by the total number of visitors to the same website. At the point of sale, the principle is the same. You can calculate your bounce rate by dividing the number of visitors who have only visited one section by the total number of visitors to the shop. This is a key factor in identifying the point at which there is a break in the sales journey.

For department stores, it's also an opportunity to see which areas are hot and which are cold, and which customers don't make a purchase because of a lack of advice. This stage requires fine-tuning and a high degree of customisation of the tool.

4. Personal data

This is a bit of a departure from the classic data capture framework. And also from the classic legal framework, since this requires customer consent under the RGPD.

Personal data is that which enables you to be identified: name, e-mail address, telephone number are among the most obvious. For the shop, it is intimately linked to the purchase and to building customer loyalty. And as it is often the case that the most loyal customers are the ones you need to invest in the most, this data needs to be handled with care.

Don't ask too much (do you absolutely need to know the dog's age?) but link it to all the data at your disposal: previous purchases, purchasing channels (website, shops, etc.), sizes purchased, etc.

The challenge is to optimise this capture and retention. It can be monetised and gamified.

5. Qualitative data

No good tool here. And the one that tells me about NPS with three buttons... 😡

This is the ultimate layer. The one that is not possible today on the web. Not even the most powerful website traffic analysis tools. It's about providing the nuances and human filters on what customers liked or didn't like. This can take the form of sales feedback, information added to customer profiles, satisfaction questionnaires, an NPS that has been worked on, or even mystery shoppers.

The important thing is to take these factors into account over time to ensure the brand's ongoing development.

To find out more about shop traffic analysis

This data can have repercussions on all your processes. Your logistics of course, your production chain, your creations and your strategy. It's also the ideal complement to the data you collect online. All that's left is to enlist the services of the right ERP.

The data collected should provide clues as to how to better capture the potential of a sales outlet. It can never be used to get away from the basics of sales or location. Pop-up store testing can therefore be used to collect data and test different types of location to see which are the most efficient.

How can you use website traffic analysis to benefit your shop?

As you will have realised, the data collected online and in person complements each other. Does measuring performance at the point of sale seem clearer to you? That's perfect. On the other hand, is analysing your online traffic still a mystery? Let's take a look.

The first step is to equip yourself with website traffic analysis tools. These will enable you to identify your traffic sources, the type of audience you have and analyse their behaviour towards your offer and yo

There are 3 of the most commonly used tools: Google Analytics, Google Search Console and Google Data Studio.

Google Analytics is the most widely used tool. Thanks to tags placed on your website, this tool enables you to track every single interaction that web users have with your site. Total number of visitors, search engines used, web pages consulted or even the length of their session... everything is scrutinised. And although the RGPD has considerably reduced access to user data, google analytics is still a mine of information for drawing up a typical visitor profile. This information can then be used to refine your targeting when you open your physical point of sale.

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Google Search Console is also an essential tool. It enables you to understand your site's audience and optimise its organic traffic. In short, it enables you to analyse the search queries that your pages appear on, and therefore the centres of interest of your visitors. This information is essential for improving your visibility on the search engine.

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Then, Google Data Studio, allows you to monitor and analyse all this data using dashboards. Free and easy to use, this tool is a real nugget for easily presenting your data and gaining a better understanding of your traffic sources.

In short, the potential for collecting data linked to your traffic is enormous. The challenge lies above all in your ability to analyse and then optimise your digital strategy. Optimised in this way, you increase your chances of generating organic traffic and therefore your visibility. And with consumers on an omnichannel journey, constantly switching between digital and physical channels... your in-store traffic mechanically depends on it. So it's up to you!