We all know business data is valuable. Data is the new oil, right?! We hear about Silicon Valley businesses that make more money from their data, than any physical business asset. We hear terms like data monetisation and think…yeah, I want some of that! But where do you begin?

Businesses can make or save money using data

Imagine the value to your business if you could:

  • See all your data in one place, so you can spot opportunities and problems quickly and easily; 
  • See where business results are good or bad across your business, so you can target your effort in the right places; 
  • Combine data across your business to identify cross-departmental opportunities;
  • Use data to personalise your products and services for your clients;
  • Create brand-new products and services for your current customers or for new markets; provide all your staff with a single view of a customer, employee, product or another business asset; and
  • Monetise your data and create brand-new revenue streams.

Most businesses can increase their profit by at least 10% using data they already have in their business, and what business doesn’t want to increase its profit?

Yet data skills, experience and knowledge are hard to find; they’re in high demand, but low supply, so they’re an expensive and rare commodity.

So where do you start?

You’ve successfully sourced, extracted, combined, processed, analysed and visualised your data, so what’s next? Now’s the time to consider if, how, when and where you can make more money for your business using data. Now’s when your data strategy truly begins to impact your business strategy.

You need to challenge yourself. How can your data help your business to make more money? How can your data help you to make smarter, quicker business decisions? How can your data help your business to achieve your goals and KPIs? Is your data a business asset?

Most or all businesses want to make more money, and data can help you do this. Data insight can enable businesses to win new clients, retain high-value clients, grow clients and expand into new markets.

For instance, it will help you to do the following:

  • See where there’s high and low performance, so you can target resources and budget in the right places
  • Use AI to identify patterns and trends you can’t easily see, so you can discover something new about your business
  • Understand who your highest-value customers are, so you can retain high-value customers, convert mid- or low-value customers to high value customers or terminate them, and offer special offers / loyalty schemes to increase customer value
  • Target sales and marketing activity to current or potential high-value customers, so you can ensure that your sales and marketing budgets deliver a higher ROI
  • Track your sales funnel and conversion rates at each stage, so you can implement specific activities to improve problem areas
  • Track your customer journey (usage; engagement; satisfaction; retention rates; and customer pause, loss and exit rates), so you can implement specific activities to improve problem areas

Another way to look at how data can help your business to make more money is to use data to analyse your performance along your customer journey. Firstly, you need to map out your customer journey. You can take weeks and months to do this to a super-high level of detail if you want to, or you can create a simplified version, as we have done in an hour:

This simplified customer journey enables you to see your customer’s steps, the channels you use to communicate with customers, and the data sources you use, all on one page. This is a great way to focus your mind on what’s important for data analysis.

Then you need to collect data on each of the stages in your customer journey, from all the data sources you can:

We recommend limiting this analysis to a defined time period – for instance, the last three months – so you don’t get tied down with lots of data. However, if your business is seasonal, or if you’ve experienced a particularly good or bad patch, you may need to look at data for a longer time period.

Then you can use the data to identify where your customer journey is working well and where it isn’t:

This will enable you to see where your problem areas are, as well as reveal the high-performing areas. You can then focus your time, effort and money in the places that will generate the most returns for your business, and stop wasting time or budget in other areas.

These data-driven actions will enable you to monetise data indirectly, through making quicker, smarter, data-informed decisions, so you’ll win, retain and grow your clients and your profit. But what about monetising your data directly?

Data monetisation! Everyone talks about it, but few businesses do it. However, particularly in the current climate, wouldn’t a brand-new source of revenue be helpful to your business? Now we’re not saying every business can monetise its data directly, as the more data you have, the greater the opportunity, of course. It’s still well worth any business considering its ability to monetise its data.

Firstly, you need to think of your data as an asset; data can seem amorphous, vague, and opaque. If you don’t like spreadsheets, numbers or coding, it could terrify you. So, the best way to start is to break down your data into its component parts: think customer profiles, social media, feedback surveys, telephone calls, online behaviour and more.

Secondly, you need to get creative with how your data could be repackaged into a completely new format, for a completely new audience, with a completely new objective. Monetising data doesn’t mean selling email addresses to dubious third parties; it could mean creating new indices, dashboards, predictive tools, market-trend reports and so on.

Using data you already have, you could create brand-new data products and services, and hence new revenue streams for your business. This could be for either current customers or new ones. It could be in the form of a dashboard, benchmark or forecast, for instance.

Many businesses are, or could be, building brand-new data products and services for their existing clients, distributors, suppliers and/or intermediaries – and they charge an additional fee for it. This could create a new source of revenue for a business, using data it already has.

Here are some examples:

Dashboard – Show your customers their product or service usage over time

  • For instance, retailers provide a dashboard demonstrating past orders and loyalty points

Comparisons

  • Reveal to your customers how they compare to other people like them
  • For instance, energy suppliers illustrate how your energy usage compares to other households of a similar size, location and number of residents

Benchmarking

  • Rank your customers against other customers on an anonymised basis
  • For instance, computer games or karting tracks often do this by showing your score on a scoreboard

Predictions

  • Provide a forecast for customers on their future usage of your product(s) or service(s)
  • For instance, Google predicts how busy a shop will be based on past activity or footfall

What-if-scenario planning

  • Show customers what would happen if they made a change to their product or service
  • For instance, mortgage providers demonstrate your final repayment amount and how it changes depending on your monthly repayments

There are two ways to deliver these new data products to your customers:

1. Integrate your new data product into your existing customer platform or user interface

2. Build a new, separate user interface for your new data product

The right decision for your business will depend on whether you have an existing customer platform, and if you do, how happy you are with it. A separate user interface is often quicker to build, as you don’t have to worry about integration with the existing platform, but it can result in a confusing user journey for your customers. This means it’s important to make the right decision for your business. We always recommend building a prototype first

for test purposes and separate from your existing customer platform, so you can seek customer feedback, test it properly and finalise the design before integrating it with your existing customer platform.

To diversify their business and increase their revenue using data they already have, many businesses could sell data insight products and services to new customer segments, to new markets and to new customers.

Here are some examples:

Trend reports

  • Provide new insight to your market using anonymised, aggregated data
  • For instance, CB Insights provides reports on the technology sectors
  • For instance, research organisations and think tanks provide reports on specialised topics

Market indices

  • Create a new metric for your market in the format of an index, quadrant, score or KPI
  • For instance, Gartner shares quadrants to compare technology solutions
  • For instance, there are indices for house prices and rental prices

Advertising space

  • Other businesses can promote products and services to your customers through your website, emails and events
  • For instance, sponsored website banners or sponsored emails

Data sales

  • Provide access to your data to third parties through an application programming interface (API) or lists
  • For instance, businesses such as Crunchbase and Equifax sell data on businesses

There could be many ways for you to productise data within your business. It’s important to think creatively and innovatively at this stage. Look beyond your market sector and region for inspiration. Think of your individual data fields and data sources as assets. Don’t just do what you’ve always done; think differently. Don’t just copy what others are doing; look for ways to lead your market. This process can be hard for a business to accomplish internally. At this stage, it may be right to bring in external help to inspire new thinking and to push for innovation.

The right product opportunity for your business will depend on four things:

1. What data do you have available? How rich is it? Is it unique? Is it at a large enough scale to be valuable?

2. What permissions do you have for the data? Have you got permission to use the data in the ways you want to?

3. What market(s) are you targeting? What will people use, value and buy?

4. What else is available in your target market(s)? What do people use today? Is there a gap?

Your business could create a brand-new unique selling point (USP) and competitive advantage for your business using data.

There is no easy answer to this. One byte of data does not always equal £10, for instance. Therefore, the best way to answer this is using six questions:

Clearly, you’ll need to make assumptions and guesstimates in this process, but we’re sure you can see that this needs to be customer-focused – your data insight is only worth what people will pay for it.

NEED SOME HELP? Schedule a free initial data monetisation chat with one of our data consultants.