Using Company Data to Grow Your Business

Marketing your business

This module discusses how to capture and use your company data to make informed and correct marketing and strategic decisions for your business.

Key learning outcomes:

  • What problem is your business trying to solve?
  • Learn about The Data Cycle
  • Data methodology
  • Correct data analysis
  • How data influences your business goals

Presentation: Using your company data to grow your business

Using company data to grow your business

Hi, I'm Victor Nichols. I'm co-founder of MacroGIS. We're a data and mapping company. So we do data analytics for a range of customers. And we're also the creator of ViewData, which is an online platform for small business to analyze their own data and gain value from their own data.

What is data?

We're here today because we want to talk about data. And before you get too worried that that's big data or something you might not understand or something that's not for you. Data is just really information. And the information that's in your business information that we normally use in our daily lives. We can use that within our businesses to understand our customers better. To reduce the cost of our marketing, so we market better, more focused. And so that we reduce the risk in our decision making process. We make better decisions.

Why should you be talking about data?

So, I guess the first thing is why listen to me? Why should you be talking about data? Why should you be looking at the data in your business?

And if we have look at this first slide that I have here, it talks about the Deloitte 2017 study into small business. And it talks about the impact of businesses not using data and not digitizing. Believe me, it's worthwhile looking up and having a read of this actual study, because it shows that the businesses that do bring digital in their businesses will thrive.

You need to move forward. You need to be moving a businesses forward. And a key part of that is the data within your business.

Second thing really is the environment we find ourselves in at the moment. With COVID-19 happening. We need to look at different ways of operating. We need to look at more advanced ways and more clever ways of using the information that we have, to save us money in the businesses when we're operating them.

And the third thing is I guess, our track record. So we've been working with businesses - at quite a complex level at times - to analyze the way that businesses operate, understand how their services are being delivered and how to increase the efficiencies in that service delivery and product delivery. Understanding their customers and market segmentation, that customer segmentation. So helping them to understand their businesses and how they can reduce the amount they're spending to get those products to their customers and finding more customers.

What business problem are you trying to solve?

I'd like to move forward now, I guess into the actual business problem.

So, as I talked about earlier, we've got a number of business problems that we're trying to solve here. When we talk about anything, we need to always relate it back what we're trying to solve, I guess.

1. Better understand our customers

And the first one, is the need to understand our customers. Who are they? I like going to exercising, for instance, but I don't like going to the gym. So would you try and sell me a gym membership? It's probably not going to work. Everyone's different. But everyone can be kind of segmented as well into certain groups. You're going to be segmented by your age and what you're likely to do, or your income, for instance.

So we can look at our customers. And the more we understand our customers, the more we'll know when we can deliver products to them, what to offer them, and the way to speak to them as well and where they might be.

2. Spend less on marketing

And so the second thing is we want to spend less than own marketing. So our customer acquisition costs need to be as low as possible. And you've probably heard of this before. Those customer acquisition costs are critical. We don't want to be spending $50 to get a customer only to have them spend $30 on us. That's not gonna work. It's not going to be profitable.

3. Acquiring more customers

The third thing of course is everyone's dream, and that's acquiring more customers. So where are they and how are we going to get them to buy from us? And if we understand our customers better, we can acquire more customers.

4. Increase the average customer spend

The fourth one is really to understand how it can increase the average spend per customer. So how can we get those customers to buy more product off us, or buy different products that we offer them? We might bundle products for instance. So that helps us as well.

5. Reduce risk

And the fifth thing is we need to take some of the risk out of what we're doing. So those decisions that we make about maybe starting up that Facebook marketing campaign, or it could be some Google ad words, or whatever we're doing, or that ad in a magazine, for instance. Are we doing the right thing? So have we got the right information to make those decisions? So when we go to bed at night, we're going okay, I know I made the right decision cause I based it on real data, real information.

The Data Cycle

Let's move on now. And we'll have a look at what we like to call the data cycle. The data cycle is a methodology of data collection, and data segmentation, and storage, and analysis, and using that within our business. And it's not something (I guess we can look at it from a resource perspective), you don't build a Facebook page and then just leave it, and then don't touch it. You're always resourcing towards it. You're always putting more information on it.

Right. Data's the same. We need to keep revisiting the data, keep making sure that that data is meeting the needs of the business. Whether that is the day to day needs, the operational type needs, or the strategic needs about where the business is going.

1. Types of data

So let's quickly go through this data cycle, I guess. So the first thing is the data types. So the types of data we collect.

Basic Data

And the first thing is the basic data. It's the basic information about a person. So it's the name, their location, you might've delivered a product to them, their age potentially, if you can get that, or an age group.

You might notice that when you go to some stores, right, they'll ask you for your postcode. They're asking for your postcode because they need to understand where you are. If they understand where you are, they've got a pretty good idea of the sort of demographic profile of who you might be, and that helps them a lot. So these big companies are using this all the time.

Business Data

Okay, then we have business data. So this is data that's specific to your business.

So it might be the type of thing products you're selling or the services that you're delivering. So it would obviously, it's going to be different from, say, a gym to an accountant for instance. So that's the type of differences.

Buying Data

The third thing is buying data - how people buy. So people buy sometimes cyclically, so they might buy at Christmas time, but not through the rest of the year. Or they might buy in bundles or they might buy things together.

So it's good to understand how they buy so that you can cater to their needs and bundle products together, for instance, and put specials on, those sorts of things.

Behavioural Data

The fourth thing is behavioural data. So information about how people behave. So you might get a particular customer segment, and they might travel a particular way to somewhere, or read a particular magazine. They might like to catch the train. There's lots of different reasons you could gather data on their behavior that's going to influence where you market. Because if you've got a group of horse lovers, for instance, and they all buy a horse-loving magazine, then that would make sense to advertise in that magazine.

So it's basic stuff, but if you don't know that then you're likely to make bad decisions that are not going to help you.


We'll move on to the next thing, which is methods. The methodology.

Base Format

And first thing is the format that you collect the data in. So sometimes it's good to have free type when you're collecting information, and sometimes it's really critical to segment. So if you're putting information into a database and you're automating that process. It's very hard to automate when your, for instance, getting someone who's entering information into a contact form, and you're just letting them type out sentences and sentence requests. It might be better in those sorts of circumstances to have a dropdown box first. Which indicates, these are the products I am interested in, so then you can collect that information.

Source Data

The second thing is the source of the data. Where is it coming from? And do you trust the source? So is the information valid? So it might come from Google Analytics. It might come from your own surveys. It might come from lots of different places. So make sure that you can trust that source.

Collection Methods

And this matches in really with the collection methods. So how are you collecting the data? I've talked to some clients who I've advised just to do surveys. Just to understand their customers. Some just to take a grip of your customers, go for a coffee and just have a chat. Sometimes it's the best way of getting, particularly with smaller groups, of getting information out of a smaller group that you wouldn't get otherwise. That you couldn't get just by trying to survey people or trying to gather that information other ways.

Quality of Information

And this all leads back to the quality of that information. So it's no good gathering information. If it's not quality information. The quality of that information you get is going to be critical when it comes to informing the decisions that you make.

Building an Information Database

Alright, now let's move on to the next bit, which is where you're going to put all this information once you've got it right. And for some it might be as simple as an Excel spreadsheet and that's fine. That's not a problem at all. Eccel and CSV files, comma separated value files, a valid methods of storing your information, and are valid particularly when a business starts out and they don't have the money to invest either time or money in a CRM. And then they want to progress through to a CRM at some point.

But wherever it is, you need to have basically one single point of truth of that data. So the information needs to be in one place. So you can always reference back to that. Now, once you've got that data in one place, then you can segment that out and pull parts out of that one database. Having that one single point of truth, you can always have that reference point to go back to.

Data Analysis

The next thing is a data analysis. Now this is really where MacroGIS and ViewData comes into there fore. Because we, as I said earlier in my introduction, we've developed a ViewData platform ,and that platform allows small businesses to an entry point, basically, where they can analyse their data. They can look at demographic profiles of people, and they can compare the two. So they can get the analytics they need to make the decisions they want to make, or they need to make.

1. Importing the data

So we'll just run a quick video now and just show you how simple this can be. And this is a video of a CSV file, simply being dragged into the browser of the ViewData
platform. And this shows how easy that data is to be mapped. And to create a visualisation of where your customers are buying.

So that CSV file simply contains a postcode of the location of the sale point. So in this case it's dummy data we put together of a cleaning products company that was selling into multiple places and posting those products to them.

So we can immediately see the information where the sales are taking place, and that gives us the information straight away. So rather than looking at a spreadsheet of information, we've immediately got a visualisation of where those sales are.

2. Filtering the data

The next thing we'd like to do is show you how we can filter that data. So we'll run the next video. Because at the same time ViewData categorises all of your information in your spreadsheet, so each of the columns within the spreadsheet, it will allow you to filter them. So if you've got, say wholesale price in there of each sale, retail price, margin for instance, then you can map your information by those as well.

Because as we know, turnover is one thing, but profit is another, right? So the things you need to be concentrating on, and this is what this sort of content will inform you, is your margins and your profit. So where are you, not just selling the most product, but where are you selling the most profitable products? And that's what really matters.

3. Comparing the data

The third video (quick video we've got here) is a video of how we compare that to a demographic profile of the particular person. So if our customer is likely to be female, within a certain age group, we can easily find them, across the whole country. And we can see the highest concentrations of that particular type of person where they're located. So if I'm trying to sell products to that person. I know exactly where to market my products to.

Business Goals

The last thing I would like to talk about is where does all this feed into? Obviously it feeds back into your business, but there's really three parts of your business you want to be looking at.

1. Operational and day-to-day

The first is the operational, and the day to day. So, it's about the sales and the decisions you're making on a day-to-day basis. So they might be where am I going to market to? How much am I going to spend in certain places? Which products am I going to market?

2. Strategic

The second thing is the strategic. So what is my future going to look like? Where am I going to take this business? Am I bringing new products online? Am I going into new areas? Am I thinking about opening up a second store? And if I am, then where should that store be? They're the strategic decisions you want to be making, and they're really important to have really good information around those, before you make those decisions. And make informed decisions and take that risk out of your business.

3. Shiny opportunities

The third thing, and this is really important, is that we all have what I call the shiny thing. Those things are opportunities that come along, that you just go, well, I can't resist that. I'm going to put a little bit of effort into that and see where it goes right now. That might not be within your strategy, but they certainly might be opportunities that you can't resist that present themselves. And when they do present themselves, you want to have the information at hand so that you can make a good decision on whether you're going to forward with those opportunities.

And it's really important to understand, the information that you've got and the information you can use to make good decisions about whether you move forward.

Repeat the data cycle

So the interesting thing about this whole thing, and as I said at the beginning is that, is that this is a cycle. So it's not something that you go do once. And then you forget, because once you've been through this process of collecting an amount of data, you want to continue it.

So businesses change. Businesses change every day. They change every week. Some go forwards, some go backwards, but they rarely stay in the one spot.

So the trick is to keep revisiting this, because those operational, strategic and opportunity within your business will inform the types of data that you need to collect next. So if you don't have the data to make the decisions about them, then you need to drive that into your data collection process again, and basically start that process again. Okay. I don't have that information. I need to make the decision yet. I need to work out a way of collecting that. How am I going to do that? Where am I going to get the information so I can make a good decision about it? Which is critical.

So this whole process goes round and round, and it's just a continuation. Basically the same, as I said about like Facebook. You keep feeding it. You keep putting information in there. You keep doing that and you'll end up being successful. Alright. That's about it. Enough probably of me rattling on about data. I hope you got something out of it.

My contact details, will be displayed I'm sure. And I'm happy to have a chat, at any stage, to anyone who thinks we might be able to help them more, who has a question about data and just doesn't know where to start. So that's it for me. And thanks very much for listening.


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