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By Fran Quilty, CEO and co-founder, Conjura

Due diligence has always been a key part of the overall investment or acquisition process, but data has taken this up a significant notch. While human chemistry and killer marketing materials still have their parts to play ahead of M&A or a funding round, an investor should now spend more time evaluating the target’s data than the senior leadership team. Indeed, data should be the defining factor between a deal or a dud.

The four pillars of due diligence – legal, operational, commercial, and technical – still stand. However, savvy investors will be looking to the data to identify where the opportunities for future growth lie  and benchmark that potential against the target’s peers.

But it’s not just the data itself that should be reviewed, it’s the data infrastructure too. How data is captured, stored and managed demonstrates how well-prepared a business is to use that data to inform its longer-term strategy. This is a key measure of value, especially in a competitive sector like e-commerce.

Understanding where a business is on its data-transformation journey helps the investor understand if the target has been valued fairly and whether it’s a safe bet. Whilst the data itself is immensely valuable, the processes and thinking in place should be viewed as equally important when it comes to reaching a final decision.

Think longer-term by looking beyond revenue figures

Revenue figures only tell half the story in a digital-first world. As we’ve seen, the bigger picture is how successfully a target can ‘read’ behavioural data to uncover growth potential at a customer, cohort, product, or industry level.

This is predicated on a business having a sufficient volume of historical customer data and the means to analyse it at a granular level. In practice, this means having a  firm handle on unit economics to react to customer and competitor activity; for example, they should be tracking metrics like gross margin, conversion rates, cost per acquisition, customer lifetime value and so on.

Investors should work on the assumption that this level of commercial application of data is now a given. If the target doesn’t know it’s CPAs from its CLVs then that’s a red flag.

Tier one targets will also have the ability to use predictive modelling to forecast and plan for growth. So, ask for evidence of how data science is being used – or will be used – to inform strategies for the mid and longer terms. Ideally, the target should be able to demonstrate how this informs factors like product diversification to grow share in the domestic market, and/or to guide internationalisation.

A well-run business has nothing to hide

Data transparency has profound implications, particularly for the traditional three-step acquisition process, as it renders the marketing phase a mere formality.

Data due diligence doesn’t have to take months and an army of auditors. There is now a wide array of due diligence tools available to acquirers that plug into the APIs of their target’s ERP and related cloud-based systems. This allows  (anonymised) unit economics to be analysed directly – and on a ‘live’ basis – so there’s no gaming the system.

Any and all assertions on performance and growth made by the target  can thus be qualified quickly and easily. Digital due diligence has become purely a set of checks and measures.

The data warning signs to watch out for

Businesses that aren’t data savvy can easily fall into the trap of making poor qualitative assumptions, notably about target markets and audiences. But there are other ways to spot the bad apples.

Firstly, pay attention to how data is stored, and managed within that set-up. Data hygiene can be a powerful indicator of the quality of the business attitudes to data, so watch out for data duplication and inaccuracies.

Next, check how often data is reviewed to spot opportunities as they emerge or to identify and react to anomalous trends that could result in lost sales. At the most basic level, this should be done on at least a daily basis. If not, this raises questions around a business’ agility – and its leadership.

Ask what metrics are most important to growth? The ones that should be demonstrably front of mind are repurchase rates and lifetime value metrics . Not taking your high value audiences into account highlights poor business acumen.

Both customer acquisition and retention marketing strategies should clearly be led by data to ensure outreach strategies are balanced with ROI. Be on the lookout for any evidence that  customer acquisition costs are regularly – or indeed ever – more than the purchase price.

Data culture, or ‘me’ culture?

How data is viewed within the business culture is a good way to gauge how far along the target is on its data journey. If the  C-suite doesn’t understand, or appreciate data then the growth potential is immediately at question.

Also, look for how teams collaborate around the data they hold, the organisational KPIs and remuneration structures. The best target businesses share data and work together towards common goals and rewards. Any suggestion that data is held within departmental silos could be a clue you’d  be investing in a company that is plagued with internal politics.

Thinking big? Start small

We’ve all heard data is the digital equivalent to gold, but even businesses with a stockpile like that of the national reserve need to have the means to extract, analyse and act upon it. Any target should be measured by its potential, but if they can’t access it, then its value is questionable at best.

It takes time, energy and (most importantly) money to get to the inherent value in data, and if the effort is going to be too significant to see a reasonable return, then it is often prudent to step away. From that perspective, the best targets are often the data-savvy challenger businesses over the market leaders

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