How to swim in data and not drown in it

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Managing data is about asking the right questions. Whether you are an eCommerce or a service provider customers won’t wait for you: use data to move faster than their desires. 

“I’m not happy unless I have a line of customers stretching out the door.”

Those were the words of a former acquaintance of mine describing daily life at the coffee shop she ran. Although I understood the sentiment (every business wants lots of customers) at the time I thought it was, as we like to say here in the UK, a bit daft. 

I don’t think I have ever met someone who is happy to be kept waiting (shout out to all my readers on Death Row in the US – I’m not talking about you, fellas). So why would a business leader be happy with something that has the potential to leave customers feeling unhappy? It just didn’t make sense.

A couple of years later, that same person sold their business at a loss. Then things made a little more sense. Stupid is as stupid does, I guess.

The quick and the dead

The expansion of eCommerce in recent years – into new product categories and into new customer segments – has demonstrated many things. One of them is that customers do not want to be kept waiting. 

Webpage won’t load? Too bad, customers will click away. Items back in stock next week? Too bad, they buy from someone else. Inflexible delivery options? Again, you’ll lose out to someone else. 

The global same-day delivery market is predicted to be worth $132 billion by 2026, according to one report. That’s an annual growth of 50%. Maybe you can’t offer same-day delivery. Maybe that means you are going to miss out. But that doesn’t mean you shouldn’t be investing in the right tools and technology to offer your customers the very best version of your business.

Because, whether it’s a coffee shop, an eCommerce site, or a delivery, people don’t like to be kept waiting.

Data, data everywhere

The technology needed to eradicate unnecessary waiting time has never been easier to configure or cheaper to buy. Five years ago, most of the delivery sector watched in silent awe as DPD routinely sent SMS updates to customers telling them what one-hour window their delivery would fall into, along with options to change the delivery – on the day itself

This is still a great service and DPD is still a great company. But the technology is no longer revolutionary. Honestly, any delivery company not providing this service is inviting trouble to find them.

At the heart of any tech-based approach to improving the delivery experience you will find data. Customer data, sales data, retail data, order data, driver data, traffic data – you get the picture. All kinds of data. 

Luckily, or unluckily (it all depends on your circumstances), every business is surrounded by data. Customer data, sales data… oh, I’ve already said that. 

Now, only one thing makes data valuable and that’s being able to extract insights from it. Data is like a big book of answers. Your job is to ask the right questions. Fans of the author Douglas Adams and the Hitchhiker’s Guide to the Galaxy will know the importance of the number 42.

If you are unfamiliar with this, let me explain – in brief. Some people build an enormous supercomputer called Deep Thought. Then they ask it a question: What is the answer to the great question of life, the universe and everything?

Deep Thought tells them the answer is 42. Funny, no?

Some questions are dumb after all

Whether you think it’s funny or not is none of my business, of course. I’m not here to judge your sense of humour. But I think it’s a delightful way of demonstrating that if you ask silly questions, you get silly answers. 

Back to the issue of reducing customer wait times. Let’s assume you have this problem: deliveries simply aren’t getting to the customer on time. First you have to understand what’s causing the problem. Only then can you start to fix it. 

For a business getting packages from A to B, understanding that there is a road closure, or there are too few drivers, or some vehicles are waiting to be repaired might help. You don’t need to be a computer scientist to solve problems like that. But if you need to do something a little more nuanced, maybe deciding where to keep stock or where to keep vehicles, or even what size vehicles you really need, you might. 

For the woman who couldn’t make a profit selling coffee, I don’t think any amount of data analysis would have helped. But a few more baristas and a few more cashiers might have meant a faster-moving line of people and more customers. Who knows?


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