Existing customers – why they don’t shop like prospects

It may not come as a complete surprise to be told that your existing customers behave differently from prospects – i.e. people who have never purchased from you before. In fact, the differences are very pronounced, especially when you look at customer journey patterns.

At UniFida we provide technology to help clients capture these customer journeys and then we use AI to analyse them. This enables the true value of different marketing investments to be understood and highlights the journey interactions that are most likely to be successful.

In our study of actual customer journeys, some of the findings are surprising. Possibly the biggest is that existing customers take longer journeys to the point of purchase than prospects. In fact, we found that not only are the journeys longer when measured in days from initial activity to final sale, but so too are the number of sales steps (events) in the journey.

Customer Journeys – New vs. Existing Example

customer type sales info

You can see from our analysis that existing customers take on average 29 days, whereas new customers take three days.

As the chart below shows, many prospects buy within just one or two sales events.

customer journeys diagram

Another key finding is that different channels work better for prospects than for existing customers. Search engines and TV can, for instance, be key for prospects, whereas direct channels like email and catalogues work better for customers.

Sales value by media chart

To some extent this is because catalogue and email are “channels of choice” for customer marketing, and hence drive more sales, but also pay per click (PPC) is used more often by prospects.

Different strategies

Given these facts, it’s clear that very different contact strategies are needed for the two different groups. As existing customers seem to prefer the long haul, the challenge is to keep them sufficiently interested during their journeys. This is where emails and texts come in, particularly when the customer has visited your website and not purchased, and also when you want to discourage them from using PPC by offering click-throughs from an email.

By contrast, prospects are more likely to swoop down on a purchase. They may have started their journey as unrecognised browsers, but when they come back to your website conversion techniques, such as website personalisation, become more important. When prospects are on your website there is no time to be wasted.

Example customer journeys

Below are some customer journey examples that illustrate these points. The top two journeys are for existing customers and show the interplay between different channels after a catalogue has been sent to them. We have chosen two particularly long journeys to allow more steps to take place before the purchase.

In the first journey, social media helped close the sale, whilst in the second it was email. Both existing customers used search even though they must have known the name of the company they were looking for, although they may have been looking for alternative suppliers at the same time.

Example: Existing Customer Journey 1

customer graph

Example: Existing Customer Journey 2

customer graph

The next two journeys for prospects (new customers) are much shorter. The top one started with the prospect searching and the sale being closed with an email, so he/she must have provided their email address on the website when visiting. In the second case there were two click-throughs from social media followed by a direct entry a day later.

Example: New Customer Journey 1

Customer type and channel graph

Example: New Customer Journey 2

Customer type and channel graph

What these charts reveal is just some of the complexity, often ignored, surrounding customer journeys and the importance of recording them so that they can be analysed.

By understanding which pathways lead to sales and which don’t, marketers have a far greater chance of making the right moves to convert prospects, and customers, to purchasing.

 


UniFida logo

UniFida is the trading name of Marketing Planning Services Ltd, a London based technology and data science company set up in 2014. Our overall aim is to help organisations build more customer value at less marketing cost.

Our technology focus has been to develop UniFida. Data science business comes both from existing users of UniFida, and from clients looking to us to solve their more complex data related marketing questions.

Marketing is changing at an explosive speed. Our ambition is to help our clients stay empowered and ahead in this challenging environment.


Marketing Metrics – why do they matter?

When it comes to measuring marketing success, there’s no doubt that marketing metrics are crucial.

Every company will have its own specific marketing metrics requirements. Analysing what these should be, and then having them delivered in a timely and reliable fashion, is vital for the success of every marketing department – and ultimately the company that it is serving.

To show the value of marketing metrics, let’s compare the fortunes of two different companies. Company A had a good set of accurate marketing metrics and used them well, while Company B had some faulty metrics and decided to be guided by them, with unfortunate consequences.

Company A

This company makes its own products and sells them directly to consumers globally. When the Covid pandemic hit they found that there was a massive upsurge in demand. By the end of 2020 they had sold 2.09 times more than the previous year. By the end of 2021 that had risen to 2.24 times.

However, their top priority was to manage supply and demand to keep the time lag between orders and delivery as tight as possible. This meant managing the amount spent on recruiting new customers and on communicating with existing ones.

Fortunately, they had historic marketing metrics that went back five years. These reported month-on-month sales from existing customers compared to new recruits, and which previous years those customers had come from. Once they knew how much the effects of Covid-19 was uplifting existing customer sales compared to previous periods, they could accurately forecast demand from existing customers for the rest of the year. This gave them a clear indication of the level of new recruits required to fill the factory capacity.

The net result? They were able to fill the factory whilst minimising their marketing spend and achieve a very strong ROMI (return on marketing investment).

Company B

This company also manages their own production, but they had a faulty metric. This was the sales value they were getting from customers to whom they had sent a catalogue. There were two reasons for this:

  • the lack of can accurate single customer view, which led to multiple duplicate records, and
  • an inaccurate match-back of those mailed to people ordering.

The result was that their metrics were reporting a much lower return – in fact, one-third of what it should have been on catalogue campaigns.

This led to a decision being made to abandon catalogues in favour of email communications. However, the company had not been particularly successful at collecting email addresses, and as a result there were only 14% of active customers for whom they had email addresses and who had not opted out.

Despite a very high volume of emails being despatched, the overall order rate in each year, from existing customers began to decline. Over a five-year period, it had sunk to a half of what it had been at the start.

However, because they were successfully recruiting new customers, the actual order value from existing customers kept going up, so nothing was noticed. In other words, instead of using the right metric – i.e. what proportion of the customers you start the year with go on to order in that year – they used the wrong metric, which was simply the absolute number of existing customer orders.

The net result was that Company B lost several million pounds worth of potential sales from existing customers, whilst not even understanding that this opportunity had been missed.

So, the value of accurate marketing metrics is clear. Analysis of those metrics is crucial to the success of your marketing activities – and your bottom line.


UniFida logo

UniFida is the trading name of Marketing Planning Services Ltd, a London based technology and data science company set up in 2014. Our overall aim is to help organisations build more customer value at less marketing cost.

Our technology focus has been to develop UniFida. Data science business comes both from existing users of UniFida, and from clients looking to us to solve their more complex data related marketing questions.

Marketing is changing at an explosive speed. Our ambition is to help our clients stay empowered and ahead in this challenging environment.