In Part 1 of this post I shared how smart brands and advertisers are obsessively using customer data first to drive their communications and marketing strategies. The days of buying mass 'targeted' reach, without customer intelligence seems increasingly old fashioned, yet many many brands still buy commodity packaged audiences from media owners as if they were the holy grail 😂
This brings me on to the definitions we use for groups of people that we wish to target. In marketing and communications we use many different names for these groups - most commonly Audiences, Cohorts, Customers and Segments. On the surface these definitions are interchangeable and loosely used to define a group of people that we want to send messages to. However, they can actually be very different depending on who you ask and what role they have within the marketing and communications team. If you ask teams responsible for awareness and acquisition, you will hear the term Audiences being used. This is a non-personal expression because we know very little about this group beyond their bundled interests e.g. car buyers or 'in-market' holiday buyers (yes they're back!). If you sit in a start-up growth team then you will often create and monitor Cohorts in tools like Google Analytics to create a tribe of similar people that use or buy your products. It's no coincidence that Google's post cookie targeting solution is expected to use cohorts, because the term transitions nicely from 'cohort intelligence' through to buying 'cohort ads' (in Google of course).
Over the last 6 months I've been working closely with clients in the customer data space, evaluating the people, process and technology that enable brands to switch to a new marketing rhythm and to become customer data first in their thinking. This is not an easy thing to do but there are some common themes amongst those that think this way, most notably their attention to Customers and Segments. What do my best customers look like? Is my segmentation strategy fit for purpose? How do I segment prospects based on my best conversion path? This type of thinking is usually initiated in CRM and Customer Value Management teams, yet increasingly this essential knowledge is being used across the whole organisation, in particular by smart marketing teams looking to gain a competitive advantage.
This attention to detail and developing a marketing rhythm using customer data is absolutely critical to success in a post pandemic world. Digital touchpoints are increasing exponentially as the world moves further online, so failure to capture this untapped goldmine of intelligence will see many brands fall further behind. Just look at Shopify who grew by 86% in 2020 - a whopping 457 million people visited a Shopify store last year! We must also consider the ever changing landscape of adtech - only yesterday Google announced that once third-party cookies are phased out, they will not build alternate identifiers to track individuals as they browse across the web, nor will they use them in their products. Google have an uncanny ability to 'predict' the future regulatory landscape, so when they announce that they will be deepening their support for solutions that build on first party customer data, I for one would not bet against them.
To enable this new capability in your organisation you need to have the right teams (the people), working in a new marketing rhythm (the process), using the right data and technology. When you combine these elements it becomes much easier to build out a customer data first strategy which delivers new customer intelligence and advanced segmentation. To find out more about this approach and how to apply the best people, process and technology then please get in touch email@example.com