Data has been at the heart of many of ECI’s most successful investments over the last 40+ years, from past investments such as Bounty (proprietary data on virtually all UK births) and ChartCo (marine navigation and regulatory data), to those in our current portfolio such as Media iQ and Avantia, both of which run massive data lakes to power their businesses.
However, we believe the opportunity to create value through data is now greater than ever before. The volume of data generated globally continues to double every two to three years[1], with capacity to store this data rocketing and the associated costs plummeting (despite fears over the future of Moore’s Law). What’s more, rapid advances in data science and AI mean that the insights that can be generated from this data are becoming ever more valuable. Whether you believe that it is the new oil or not, the rise of data is a phenomenon that cannot be ignored.
Indeed, investor interest in the space has never been higher. According to data from Pitchbook, private equity investment into data businesses has risen 63% over the last five years[1]. 2017 also saw the birth of Softbank’s $93bn “Vision Fund”, the largest VC fund ever raised, with a key element of their mandate being to invest into data businesses and data-driven business models.
So, what it is that investors like about this space and what can entrepreneurs and management teams do to maximise the value of their data businesses? Broadly speaking there are two key characteristics that attract investors to B2B data businesses, resilience and scalability.
Resilience through subscription-based revenues
In terms of resilience, B2B data businesses tend to operate a subscription-based revenue model and therefore generate high levels of predictable, recurring revenue so long as customer churn is low. Where data is considered ‘must-have’, and particularly when it is integrated into business workflows, churn is indeed often very low – the caveat being that one must also consider factors such as industry resilience (e.g., will many customers go out of business in a downturn?) and competitive threats.
Scalable business models
In addition, many of the costs associated with running a data business, such as data gathering and analysis, IP development, and content distribution are often relatively fixed. This means that, as data businesses grow, they benefit from significant operational leverage and are able to improve their profit margins over time.
It is therefore not surprising that this is a market that has piqued the interest of investors. But what drives valuation differentials within this pool of businesses? Whilst the normal considerations such as the quality of the team, growth, and profitability are, of course, still important, there are a number of specific other factors.
Attractive end market
First, investors will consider the attractiveness of the underlying market being served by the data provider. Is the market stable and growing? Is there an increasing need for, and spend on, data services? Is there lots of headroom left to go for, or is growth being driven by market share gain and price increases? (One of the issues for companies selling ‘must have’ data can be that they already have the market fully penetrated).
Strong customer value proposition
The value of your data to these end customers is also a key driver of value. The further your data is to the “must-have” rather than “nice-to-have” end of the spectrum, the higher the value that investors will place on your business. Feeding into this is the degree to which you are embedded within the workflow of your customers (i.e. how disrupted would their business processes be if their subscription to your product or services were cancelled tomorrow?). Clearly these factors can be difficult to quantify, but KPIs such as customer churn, usage frequency, and the ability to increase prices over time, as well as customer experience metrics such as net promoter score can help to paint a picture of the value you are adding to your customers.
High barriers to entry
Barriers to entry are also an important consideration. These can be built through the data gathering process, adding value to data, possession of historic data, or through scale. Unique access to data can be a powerful way to build entry barriers, and generally involves having a proprietary method of collection such as installed hardware or exclusive relationships with underlying data sources. In addition, competitive advantage can be built by adding value to data through IP, often in the form of an algorithm that adds value to the underlying data (e.g. forecasting future demand). Finally, breadth of data and scale can play an important role in building a robust competitive position. This is particularly relevant for areas where historic data is valuable, or where data is user or customer generated (resulting in network effects).
Creating value in your B2B data business
So, as the owner of a data business, what can you do to maximise value? First, think about how to make the business model more attractive. How can you make your data more ‘must have’ to your customers and how can you then further embed it into customer workflows? How can you transition to a more visible (subscription-based) revenue model? Secondly, have a clear and credible growth story. If you are capping out on growth in your core market, can you create product extensions to serve existing or new customers, or can you expand internationally? If so, it’s useful to have built some track record of growth here before you look to sell your business.
In summary, we believe that significant value will be created by data businesses in the years to come. As a growth-focused investor, we are hugely excited by the opportunity that it represents for businesses and are always interested in meeting founders and management teams that share this enthusiasm.
[1] Pitchbook data run on private equity deals in data globally from 2013-17
[2] McKinsey Global Institute, The Age of Analytics: Competing in a data driven world (Dec-16)
