There is a lot of talk in our industry right now about data. Manufacturers want data from their wholesalers, wholesalers want data from their customers and everyone wants data from their competitors.
At JJ Food Service, we have entered our 27th year in business and with more than 60,000 customers we’ve accumulated a huge amount of valuable data. Any wholesalers with a good history of data is sitting on a goldmine but even so, when it comes to making use of it, it can be difficult to know where to start and what will truly add value.
The reality of data is that no one really wants to share it – even basic elements like products’ prices. Can you believe that we are one of the wholesalers that have a transparent pricing system? Anyone can view our prices online and we continue to offer a discount to customers that click and collect. In this rapidly changing and very dynamic business environment data insights are absolutely paramount for better customers’ and suppliers’ engagement. But traditional approach of keeping it close to your chest for internal only Business Intelligence (BI) usage is no longer going to be enough. It needs to be shared in the appropriate format amongst all the trading partners for better value all round.
Like many delivered wholesalers, JJ operates 24/7 and is Omni-channel, covering the entire supply chain from goods being delivered by manufacturers to collating and shipping goods out to our customers. As with any complex supply chain, something can always go wrong, and with eight different branches across the UK to monitor, all day and all night, data is critical in helping us to continuously learn what we are doing right and what we could do better. Let’s face it; our customers have a lot of choice in which wholesale suppliers to use so no one can afford to make the same mistake twice.
Data helps us to see clearly
So how does data help us? JJ Food Service is using Microsoft Power BI technology to gain a deeper understanding of customer data. It gives us a clear, real-time picture of everything from customer behaviour and product success to issues with manufacturers. Bring all that information together and you get a very clear, three-dimensional view of how to give customers the right services exactly when they need it.
For instance, we use data to optimise how we buy products – we will know well in advance when a product is due to run out and if something is out of stock, not only is it physically impossible for the customer to order it, our online ordering system and our telesales staff can recommend alternatives – so we don’t lose a sale and the customer stays happy.
Who’d have thought that sweetcorn and washing up liquid had anything in common? But they do and knowing this has helped us to increase basket spend.
Our machine-learning technology using Microsoft Azure Cortona Analytics Suite can also predict the customers’ shopping list – so the most frequently bought items appear when they visit the site. It can also be useful to share what other customers have bought. Our ‘frequently bought together’ function on the website and app makes product suggestions based on purchases that other people in the same market have bought.
Runtime customer profiling
Data can also help us to profile customers on the spot, which can be useful when caterers often change their menus and markets. For instance, we might have a customer who over time has expanded, refurbished and completely changed his business model from being a small café to a large fine-dining restaurant. He hasn’t told us this but by looking at his shopping basket we can see that he has gone from purchasing sausages, eggs and beans to fresh lamb, sirloin steak and gluten-free chips. He hasn’t told us and we haven’t asked him, but the machine has figured it out. And we can respond accordingly by sending him the correct promotional materials targeted at this specific sector.
Do you know which customers are going to leave you before they do? Quite a tough challenge but we try to stay ahead of that game too. Another way we use data is to conduct a ‘customer-churn analysis’, which is basically a deep look at who is likely to stop using you. We can already see that they may have experienced difficulty with our delivery personnel or the product range has not been suitable. Monitoring this in advance helps us to be proactive in helping customers solve their problems.
Having a wealth of information about your customers can also make it easier to categorise them. But prioritise them at your peril – regardless of how big or small a customer is, they should all be equally important. We have small customers with hardly any storage space who buy little and often whereas larger customers, such as other wholesalers, will buy in bigger volumes but buy far less frequently. Data can help you to see what these customers are really worth to you regardless of what they look like on paper.
What’s next for JJ Food Service?
So what do we have in store for the future? We already have a centralised data point giving us a single version of the truth. The next step is to continue fine-tuning an already heavily optimised business. When businesses say that have improved a process by 25% of 50% that should tell you that the system they had in place to start with was pretty bad. We are looking to make single digit improvements, from paying suppliers quicker to answering the phones faster. Lots of very small improvements will eventually make a very big impact.