There aren’t many positives to take from 2020 but one well-documented outcome of COVID has been the acceleration of businesses to a digital-first model. While this has benefitted many, particularly in the e-commerce space, the challenge will be maintaining growth for the longer-term.
Now is the time to capitalise on this shift in consumer behaviour. But with only so many customers to go around, success is dependent on becoming the go-to brand in your given category. With so many businesses pivoting online there’s a limited window to stake that claim. Often this means future-proofing the digital experience, which needs a cash injection.
Businesses that don’t have significant cash reserves will typically look to third-party funding from Private Equity or angel investors to fuel their growth plans. Before embarking on a funding round it’s good practice to reflect on exactly what indicators a potential investor will be assessing before reaching a decision to part with their cash.
This will be based on data and, in particular, how this translates to growth potential. In practice this means making sure your business data and data management processes are watertight before initiating a conversation.
An investor will be gauging where your business is on its data-transformation journey and where it can go. If we break this down into five stages, the first step could be – kindly – described as chaotic, which suggests the business realises low value from data. Any that aspires to become data-driven needs to reach the other end of the scale, intelligent. This confers significant competitive data-led advantages.
In a highly competitive online market, there’s little point in even applying for funding unless your business is at least at the mid-way point on that journey.
Investors will be doing due diligence to benchmark your business against others in your category in terms of long-term viability, both in terms of current and potential performance. Take note, they will work on the assumption that the commercial application of data is a given in the current landscape. A baseline translates to a functional use of data, which is demonstrably driving revenue growth.
There are a number of red flags investors will be looking out for that reveal a business doesn’t ‘get’ data:
Take note Public Health England, if this is being done on Excel then you’re probably beyond hope. At the bare minimum this data should be held in a fit-for-purpose database and, if siloed, there should be the potential to feed into the broader marketing and sales suite. The goal should be an integrated data architecture that allows a business to automate reporting systems and thus speed up analysis.
Agile processes rely both on the granularity and the speed of reporting. How long it takes a request to be turned around is indicative of the quality of a business’ technology and its people.
A well-run business should be collecting and analysing data on a daily, or at most weekly, basis. Good data management allows you to respond to customer and competitor activity in the market. It also allows you to proactively identify and act upon anomalous trends that could result in customer churn. This could be as simple as a glitch in a payments system, or a broken affiliate link.
Investors will look beyond the immediate measures of success though. They are interested in what they refer to as unit economics, this takes in factors such as: the cost of acquiring customers across different marketing channels; the lifetime value of customer cohorts, by channel, by geography; the products they bought, using which device; re-order rates – and more. You can be sure they will be asking for these types of metrics on a regular basis during the funding application process. If it takes too long to supply that information then the process can come to a grinding halt.
There’s an oft-repeated phrase in the data sector, ‘rubbish in, rubbish out’. You need to be able to track and act upon the right data to achieve stated objectives – whether that’s to reach new customers, or to increase the frequency of sales to existing customers (for example). If the data you’re capturing doesn’t address your goals, time spent on analysis is simply wasted.
Once you know exactly what metrics you need in line with your growth strategy, the next step is to ensure data is cleaned and de-duplicated and you’re using the right tools to extract the value. Many of the tools on offer to measure the data only provide estimated returns, rather than plugging in direct to e-commerce platforms to provide actual revenues. Most importantly, the person doing the analysis understands how to use those tools. Analytics is all-too-often foisted on the marketing team, but that’s a big ask if it isn’t their day job.
Not all customers are created equal, but some businesses are too keen to pursue new customers, even if they’re unlikely to make a repeat purchase. Not taking lifetime value into account demonstrates poor business acumen – especially if the cost of acquisition is more than the purchase.
When it comes to data, the devil really is in the detail. Demonstrating you truly understand what your data is telling you can be the defining factor between a successful application, or not.
Investors will be looking for evidence you know what you’re doing, which means no data duplication, no inaccuracies and no trying to game the system. For instance, in the case of a subscription service an indefinite postponement should be recorded as a lost customer, rather than an active one.
The online space, and in particular e-commerce, is exploding as businesses large and small go through the ‘COVID pivot’. There will be winners and losers in a finite market and growth will be driven by data. Investors are acutely aware of this and will not part with any funding unless they are reassured by your data strategy.
Before engaging, it’s therefore worth bearing in mind a ‘colourful’ military adage known as the ‘six Ps of planning’ – proper preparation prevents p***-poor performance.