How many times have you read the words ‘artificial intelligence’ or ‘machine learning’ this week? If you read the industry press then we’re willing to bet that it’s at least a handful.
AI and machine learning are sector buzzwords. They seem to be everywhere. They are this season’s must-have accessory.
But are you up to speed with what they actually mean and what they can do for B2B wholesalers? Do you really need whatever it is AI and machine learning will bring to your business? Are you missing out on what they offer, or are you better off just letting them pass you by?
Here’s our ‘dummies guide’ to the basics, so you can make up your own mind.
Just exactly what are AI and machine learning?
Artificial intelligence is the idea that machines can learn things independently, without being told those things by us humans. The idea is that the machine comes to mimic human intelligence and is thus ‘artificially intelligent’.
Machine learning is a specific application of AI. The machines in question learn through data and then use what they’ve learned to carry out a response.
Often, in common discussion in the sector, the two terms are used interchangeably and, really, for our purposes, either is fine.
Can you give me an example of what machine learning actually does?
Yes, so let’s look at a simple real world example before we look at the B2B wholesale sector.
Let’s say you need to buy some socks off Amazon. When you go to order your favourite socks it might say ‘just four left!’. When you place your order and revisit the page, you’ll see there are ‘just three left!’.
This is machine learning in action. No-one is sitting there keying that information into Amazon’s database or coding the website you see to display the new stock figure.
Instead Amazon’s technology is looking at the database, seeing the stock figure and making the website react accordingly. When the stock figure goes down, the machine reacts again and updates the website with the new number.
And that’s not all. Now the machine knows what brand of socks you like. So, in a few months time, you might get an email suggesting you buy more of those socks. No-one has pressed ‘send’ on that email; the machine has used the data it has to produce something useful.
Machine learning in action!
OK, I see how this works. But how does it work in B2B wholesale?
In a very similar way to how it works on places like Amazon.
Your online store can use machine learning to look at all of the data you have and take actions based on that data.
Let’s say one of your customers always orders cases of Coke. They head into your app and start typing: ‘c-o-...’.
The results from that search at that point could include Coke, but they could also include ‘coffee’ or ‘cold drinks’ or maybe ‘covid masks’.
But because your online store uses machine learning, and the ‘machine’ knows this client always orders Coke, Coke would appear at the top of the list. Just like on Amazon, the machine has made it easier for your customers to order more of what they like.
That’s nice! How else can machine learning benefit B2B wholesale?
As we get more data, we’ll be able to put machine learning to greater use.
It’s possible to create ‘related products’ without any machine learning. The customer who always orders cases of Coke can easily be shown Diet Coke and Coke Zero as ‘related products’, for example.
But with machine learning we can also show that customer products that are ‘related’ because they are often ordered together.
There’s no obvious relationship between Coke and burger buns, for example. But if we start to see elevated levels of orders which include both Coke and burger buns - perhaps in the early Summer period, in time for barbeque season - then the machine can start to share this information with your customers.
The result for you? Increased digital basket values as customers are reminded what they should be ordering and what others already are ordering.
This machine learning sounds good. Is there more?
Yes, very soon we’ll be publishing a data-driven roadmap to show B2B wholesalers exactly what will be available in the future and how they can put machine learning to work. Watch this space.
