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Welcome to you our lovely listeners to the HSO Dynamics matters podcast.
Your regular sonic dive into the world of Microsoft technology related matters and much more besides.
I’m Michael Lonnon, and today I’m joined by Head of Data & Analytics Daniel Knott.
There’s a lot that’s been made of the importance of the digital journey when it comes to the customer buying experience, and in this podcast we chat about why it’s so important and what role data plays in helping define the journey.
So, grab a brew, sit back, relax, and enjoy the show.
Michael Lonnon – 00:44
Good customer experience or good product price?
Dan Knott – 00:52
Good customer experience.
Michael Lonnon – 00:53
I’d say that most people are prepared to pay just a little bit more for better customer experience wouldn’t you agree?
Dan Knott – 01:02
I would yeah, you’re more likely to go back.
Michael Lonnon – 01:06
When it comes to that experience, there’s a lot that’s been made about kind of the digital journey, particularly while I’ve been in this state of lockdown, the emphasis on improving digital engagement has sort of gone up for a lot of retailers, a lot of manufacturers, a lot of companies in general really, financial organisations and some of them are doing it really well. But in your opinion, Dan, why is it important to have a well-connected digital customer experience?
Dan Knott – 01:39
I think there’s probably two elements on this one, the first one being, you’ve got more points of entry to connect to your customer to understand your customer and collect the data on that. And the other point to that is to analyse that data to then make the experience better. And by that, you know, how do I make the experience of our customer well? That’s by targeting advertisement campaigns on products they’ve bought, understanding what their behaviour patterns are when it comes to buying, what the demographics…….. All the information that you can collect about your customer in there and how they interact with you as an organisation can only help on the other way out in delivering the best service to your customer and understanding their needs and requirements
Michael Lonnon – 02:24
I was watching the Microsoft Biz apps launch recording earlier on and they’ve launched a really nice sort of tool that (how do you explain) a buying experience tool. So if you purchase something online from say, a retailer and the information is stored, and using machine learning or artificial intelligence, it analyses kind of your buying behavior; it analyses it in such a way that sporadically will offer you up promotions based on the things that you’ve purchased over a period of time. You walk into a store and it will flag up directions of your most purchased items or the things it thinks you’re most interested in where they are in the store. It’s sort of taking that from online to in store. Technology has a much bigger picture of you as an individual. What state is role in helping piece those things together? Because technology is only one part of and it’s nothing about data, I would say. But what role does is sit here?
Dan Knott – 03:34
It’s fundamentally at the core of it if I’m honest. Because without the data, you can’t do your AI machine learning algorithms, you can’t understand your customers, you can’t get insight to that, if you’re not capturing that data. So yeah, fundamentally it’s at the very, very core. Going back to your point around the buying experience, and you know, offering promotions it is also available, I suppose to a degree, with taking technology aside, that sort of level of using data in that way. If you go to your local supermarket with your let’s call it loyalty card. Afterwards, you probably get spun out a series of tokens to get additional points and so forth. Always a winner 1000 bonus points for dish-washing salt.
That is, in essence, using data to then either upsell or to get you to buy again and in the background, it’s using the data then to calculate the probability of what you’ve bought or all the sales that you’ve gone in and you’ve scanned, let’s call loyalty card. That buying data is sitting there, it can be analysed, and it can be compared against, you know, with that demographic of you as an individual with your postcode. From there, there’s so much other data you can attach to the back. You can then start to compare your demographic, your variables as you as a consumer, against the variables of other similar like-minded demographics. So then, based upon what they might buy, you might be offered an upsell. But also looking at you’re personal buying pattern, they can see that you might like Tetley’s rather than PG Tips, and they might offer you extra bonus points to buy another pack of your favourite brand of tea. So it goes in both ways. It provides opportunity and it also provides consistency in knowing your customer.
Michael Lonnon – 05:38
And it can only do that if it has that information, if it has captured it and managed it well.
Dan Knott – 05:43
Absolutely so yeah, data there is fundamentally key to drive both of those decisions.
Michael Lonnon – 05:50
Where do tools like artificial intelligence and machine learning fit with that? I guess, as I mentioned, it’s fairly fundamental. You can have the data and you can have good analytics, but actually, because we’re talking about such vast quantities of data for a lot of organisations, you need some way of taking some of that manual element out and that’s where artificial intelligence machine learning comes in to predict some of the things that happen. What do you think? Why do you think it’s important?
Dan Knott – 06:19
The value that it adds, and I suppose going back to the point you made in which a person could look at it and offer that better value output, is probably a slightly inaccurate one on the basis that a machine can analyse in more lower granularity and more depth, to find more distinguished and undistinguished patterns in that data that a human may not find physically possible. And also the scalability. I mean, to analyse and to go to the depths of the insight that you’re after would require a lot of processing power. So that’s where the cloud, you know, in terms of Azure the scalability, of having this platform as a service, you know, artificial intelligence, cognitive services, machine learning, it’s the tools to crunch that data at scale and to provide with a reasonable accuracy of output.
Michael Lonnon – 07:15
Okay. Is there one thing that stands out above others in terms of how you can create almost a connected experience. I ask that because in a past life, we worked with a large financial service organisation. They had a problem in that they sold pensions, insurance, insurances, and (something else, I can’t remember, what was it) asset management I think they held. But they were held like almost, they were siloed, the information was siloed so the same customer, maybe a pensionable customer as well as an asset management customer. But actually, the organisation as a whole didn’t see them as one single customers or two separate customers. So they’d sell to the same person in multiple different ways.
And if they phoned into the call centre, the call centre wouldn’t know where to route them because they didn’t know where their information sat and so the experience actually was pretty poor. So from my perspective, I would say that the big problem or the best way to improve an experience is by connecting your information that you might hold on those individuals. Is there something you might advise or if you want to enhance experience, here is probably the starting point for how you might do it?
Dan Knott – 08:31
Yeah, obviously there are other box tools like customer insights is a particularly good one, where it will give you the front end to pull that data together and map and merge it together. So to get a unified customer, for their data, obviously, and the need, needs to be of a certain quality, but also not thinking that a single tool there, you most likely want to start under the hood, start utilising data warehousing for instance, to have that data stream all coming into one. To have the one customer, the joined up experience. From an analytics perspective, analyse your organisation, understand your customer and its touch points within certain areas.
Michael Lonnon – 09:19
Your looking for a single customer view effectively aren’t you and then analyse it from there from the touch points, everything else and engagement from there.
Dan Knott – 09:25
Absolutely and I guess it’s touching on that, it sounds as straightforward as that. Under the hood, there’s obviously a lot of joining up, a lot of mapping, you know, understanding customers from you’re your different systems coming in together and having some, you know, I suppose, logic to unify them into a single customer.
Michael Lonnon – 09:46
Yeah so I guess a lot of it is again as we’ve spoken about before, it’s about having the ability to get your data in order to give you that single view that enables you to analyse that information to provide more relevant more personal experiences for those individuals?
Dan Knott – 10:06
Absolutely, otherwise, when you analyse it in silo, you’re only getting a fraction of the actual overall puzzle in terms of how you can analyse. So if you’re only understanding one engagement, you’re only analysing one scenario of the bigger picture. Bringing data together is a big fundamental key for any data alignment with a business to understand their customers, their processes. It streamed all across all different areas and opportunities within an organisation. So it doesn’t just focus just purely on the customer. If you want to focus on the customer, then absolutely bringing all that data together and having the sort of I suppose, in old money, a single version of the truth. It’s a single 360 degree version of your customer and the interactions that they have with you both in store and online. You can then enhance that experience for them in many various ways with data.
Having a good handle on you data is essential to creating a seamless customer experience. But it’s also essential you have the right tools in place to enable you to crunch data at scale, and then make decisions that impact that journey.
And as Sherlock Holmes once said: “It is a capital mistake to theorise before one has data”
Keep an ear out for more podcasts in the Dynamics Matters series, just visit www.hso.com/dynamics-matters until then, take care of yourselves.