Have you ever spent weeks behind your computer, cross-referencing a customer’s shopping list to your own inventory? Want to find out how you can tackle this in a matter of days, instead of weeks? Keep on reading….
Last week we discussed the ever-growing issues around dealing with product data, and our solution to these issues: our Product Data Platform (PDP). Bad quality product data is making many people’s lives miserable, so we’re here to make sure you get to work with your data, not on your data. In case you missed it, you can read up about it here.
One of the core functionalities of a PDP is ‘product matching’. In this week’s blog we’ll tell you all about it, and how automating this can save you a TON of time and effort. To make this a bit more tangible, let’s step into the shoes of a salesperson who is dealing with a large client’s ‘shopping list’.
Imagine you are a sales manager at a large technical wholesaler. You will often get requests (tenders) from potential customers who are looking to purchase hundreds, thousands, or sometimes even 10.000+ products. You can bet you’re a** they are not using the exact same naming conventions and variables as you are, so it is going to be a TON of work to figure out which products, or specials, the client is exactly looking for, and to cross-reference these to your own inventory. Or perhaps, if you have some products available that you can suggest as a good alternative to the initial request. A PDP can help automate this entire process, enabling you to respond to these tenders within days, rather than weeks.
Matching product data is all about ‘connecting the right dots’. This sounds simple enough, but once you start thinking about the various ways that we can name a product, the difficulties start to become clear. For example, what would you call the two products displayed below? And what would happen if you sell ‘ball bearings, but a customer wants to purchase a ‘bearing’? Connecting these two dots is what a PDP can do for you, automatically
In this day and age, PDPs make use of machine learning and AI to connect the right dots to each other, by identifying variables such as:
Sophisticated algorithms are then able to match your customers’ requests to the products you have in your own inventory, based on these variables (and many more, but we can nerd out about that another day). Using these techniques, some companies are able to respond to these large tender requests up to 60 times faster compared to their competition.
And since we’re putting ourselves in other people’s shoes, let’s look at this from the perspective of the customer. Imagine sending your tender requests to a couple of companies, and after 2 days you will find a response in your inbox from one of them, and then having to wait 3 more weeks to get a response from the others. Someone just got a checkmark in the ‘pro’s column’…
Interested to learn how you can save a TON of time responding to tender requests? Feel free to get in touch with us. Maybe you can think of some other use cases where automated product matching can add a lot of value? We can think of a few more, perhaps we should write another blog about that…. Time will tell.
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