How to use data to drive business growth at every level
All data are created equal
Revenue tracking, server latency, customer feedback, viewable impressions etc all begin life as a collection of bits. The vast majority sit dormant in digital museums, never to be seen by human eyes or exploited for the latent value that they contain. I’m pretty sure this is what people mean when they talk about Big Data; massive clouds filled with 1’s and 0’s that almost no one knows how to use. Sad times.
Maybe this will change soon. But that’s a tale for a different time and a different post.
The following snippet and a diagram from another article I recently published on the topic of business growth provides good context for the remainder of this post.
Proprietary data is your unique window into customer needs. It creates competitive advantage insofar as the needs that your data reveals to you are yours alone to act upon; to create new features, services (or products) and businesses, enabling you to grow.
When people do look at data, it’s usually in job function related silos. Customer service teams look at the call centre and web-help data, marketing teams look at the campaign performance data, e-commerce teams look at the web analytics and maybe app analytics data. In my experience it’s exceptionally rare for businesses to bring together disparate data sets in meaningful ways. By meaningful, I specifically don’t mean badly designed dashboards that don’t actually power decision making. They look like this.
To me, ‘meaningful use of data’ is any use that has a positive contribution to one of the three ways you can grow a business:
- Increase usage of the existing product or service (more people and / or more often)
- Increase the value derived from each instance of use (higher price)
- Increase the utility of your business by serving a larger number of needs (new products & services / bigger share of wallet)
Data has no value without context
Knowing the bounce rate of a website isn’t going to tell you anything. Without something to compare it to, you don’t know if its good or bad. It’s just a number. You can try to change it, but you won’t know which direction you want to change it in and you won’t have a clue what you should change to make that number different. You certainly won’t realise that many people consider it to be a vanity metric these days.
What gives data context is other data. In fact my example is cheating because it used two data points, one is the number, one is the descriptor of that number (bounce rate).
How data supports business growth
Basic optimisation
If you add the above data to other client bounce rates, device info, traffic sources, time of day, week on week and year on year views then you can start to build a picture of what’s going on. Not an amazing picture, but maybe enough to start troubleshooting and improving the bounce rate. That’s pretty much it though. Even with multiple data sets — their lack of diversity makes them very limited in how they may help your business grow.
Basic optimisation might help you do this.
1. Increase usage of the existing product or service (more people and / or more often)
Basic optimisation increases the base level of satisfaction of using your product which could be a key factor in people using your product more often or it could result in higher levels of positive word of mouth and therefore more people using it.
It’s not going to make people pay more for you and it certainly isn’t going to create a new business, product or service.
Product, service or business innovation
Throw in a bunch of other data; competitor analysis, transaction history, customer ID, market trends, focus groups and the data created by your supply chain and you’re moving towards being able to create something really substantial.
Product, service or business innovation might help you do this.
3. Increase utility of your business by serving a larger number of needs (new products & services / bigger share of wallet)
Only when you look at a broad spectrum of data, in significant volume, can you start to really unpick, observe or assume (with a high level of accuracy) needs, old or new, that are being underserved. They might be closely related to your existing product and service or they might be a completely new market for you. Consider Amazon, Amazon Prime, Amazon Echo, Amazon Fresh, Amazon Turk, Amazon Web Services and so on. Cloud processing power isn’t all that similar to selling USB drives but that didn’t stop Amazon from becoming one of the biggest providers of cloud computing in the world.
Feature innovation
Somewhere between the two is feature innovation. This is a bit tricksy; not from a data schema perspective — but how it syncs with the way you choose to do it to pursue the different ways of growing a business.
Feature innovation can drive business growth in all the ways.
1. Increase usage of the existing product or service (more people and / or more often)
Introducing new features can work in the same way as basic optimisation. You might choose to release these features to your existing customer base, without a price hike (Amazon Echo gets free feature updates almost weekly). You would do this in the belief that doing so will make your product attractive to more people, make the product more useful to your existing customer base (so they use it more often), or increase the likelihood of driving positive WOM (also more people).
2. Increase the value derived from each instance of use (higher price)
The way that this is differentiated from option 3 is really nuanced. You could introduce a new feature or set of features to your existing customer base for the above reasons. However, over time you might have the data that proves that those features are highly valued by your customers. You might then use this to justify charging a higher price for your product or service at a later date, once those features have become part of the core.
3. Increase utility of your business by serving a larger number of needs (new products & services / bigger share of wallet)
Feature innovation can go a step further by increasing the value delivered to the customer in a distinctly marketable way (confusingly this isn’t the same thing as a Minimum Marketable Feature, but it’s not a million miles away). You might choose to release a feature or set of features and charge for this ‘upgrade’ differently to your core product. At this point, you’ve gone beyond feature innovation and have crossed the boundary into achieving product / service / business innovation.
Consider Netflix. The basic package gets you a great service. But for a few dollars extra you can have features like 4K and simultaneous streaming on more devices. It might not feel like it — but this new tier of Netflix is actually a different product. It appeals to a different (and smaller) group of users that have distinct needs. In this scenario, the product is similar enough that it could cannibalise customers from the basic product, but it could also bring in a whole new customer base (ones that are particularly snobby about 4k, for example). The more valuable product, at a higher price could even be different enough to change other spending behaviours (e.g. cinema-going, premium cable services, Blu-ray purchase) to help Netflix gain a bigger share of wallet.
Hopefully what I’ve explained sounds simple. In reality, connecting large volumes of disparate data sets is incredibly difficult to do. But if it were easy… everyone would be doing it ;-)
As you strive for innovation, don’t forget about what’s going on right now. If you’ve got customers that are straight-up telling you why your product or service isn’t meeting their needs, then you’ve got work to do before you’re able to invest your time and money trying to invent the future.
I’m a strategy consultant with over 10 years experience in digital and a keen interest in product strategy and business innovation. Ping me a note on here or Twitter to say hi if you’d like to chat.
