Understanding Relationships

Understanding - sThe secret to fivefold growth…

One of the Seven Habits (of Highly Effective People) according to Stephen Covey’s seminal book, is “seek first to understand before you can be understood”.

It’s one of those solid pieces of advice that relates to so many fields across the charity world: from conflict resolution and leadership, to influencing and fundraising – the better we understand individuals and groups, the more able we are to get our messages to land and, ultimately, to persuade them to give us what we want.

But there is one field where that fruitful advice seems to have continually fallen on stony ground: earned income – that oft-overlooked generator of almost half of the sector’s total revenue, and the field where, in most other sectors, that same advice has driven transformational change.

It is ironic, because it’s that desire to understand that has made “big data” so prized by fundraisers and commercial marketeers alike, and even now there are few better examples of its potential than one of its earliest incarnations: Tesco Clubcard.

Clubcard began in late 1993 as a 90-day trial, running across 14 Tesco stores. The customer got a penny back for every pound they spent using the card, and Tesco got an avalanche of data.

Within weeks the Clubcard team had identified patterns in that data, like items that were consistently missing from different customers’ weekly shopping baskets – items they were clearly picking up elsewhere.

To begin with, they sent those people special offers to try Tesco products in the missing categories and watched the data to see how many took them up on the offer, but also how many went back to their previous pattern afterwards, and how many preferred to stay with the Tesco products once they’d tried them.

By the end of the trial, the sales uplift across the trial stores averaged over 10%, but more importantly, the team had learned a wealth of unexpected things, like which products weren’t up to the local competition, and for the first time, they started to understand not just what their customers did, but why.

For the next two decades, Clubcard data and its increasingly sophisticated analytics, would drive almost everything Tesco did, from product selection and pricing, to promotions, advertising and store opening; and as a result, the number of customers they’d serve would grow fivefold.

Tesco had discovered a different way to look at their business, not merely in terms of sales and income and expenditure, but in terms of customers, choices and behaviours, and of the extraordinary value they could unlock by genuinely understanding the mindset and motivations, the priorities, pressures, and preferences of them as individuals.

Most UK charities, whether we like it or not, have at their hearts a business model: income and expenditure, and by whatever name we choose to call them, paying customers. And relationships and customer understanding are, and always will be, the currency of charity business, just as they are for every other kind of business.

Which is why it’s so surprising to me that, almost thirty years on, most charities still have an entirely transactional relationship with most of their paying customers. From service users to commissioners, from retail shoppers to individual customers, half the time we don’t even know their names, let alone what they love and loathe. Amazon knows more about them than we do.

Even in the simplest, most obvious areas: few charities have relationship owners for their biggest commissioners, more often there’s a bid written in business development, a placement or project conversation with a unit manager, a beleaguered area manager hastily preparing their performance reports and apologies when summoned to a long-overdue review meeting.

Is it any wonder charities are struggling to survive in these markets?

It really doesn’t have to be this way though. The successful examples are out there. The template is easy to follow. The value has been demonstrated time and again in the commercial world.

So, how much more data will you need to see before you start investing in “understanding relationships”?

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