26 August 2021
6 minute read
The focus on customer data and specifically the need to have actionable first-party data has dramatically increased over the past 12 months since Google announced that Chrome would no longer support third- arty cookies. But it’s not just the threat of a cookie-less world that should prompt a re-set, it’s also the desire for customers to have more control over their data and a greater imperative for marketers to deliver more connected, relevant and personalised experiences.
However, for those of us who have spent many years working with customer data, we know that collecting information on customers is the (relatively speaking) easy part. The real challenge lies in the ability to transform customer data into actionable insight that can be applied and deployed across the business to increase the volume and value of customers. This need for translation also comes at a time when there’s never been a bigger focus on data (both in the trade and mainstream press) and the potential value that it can deliver to brands.
FRAGMENTED DATA REALITIES
Faced with ever increasing volumes of data being collected, C-suite leaders are challenging marketers to become more customer-centric by taking advantage of the customer data collected and the significant advancements in data storage, processing, data science and deployment capabilities. However, whilst many brands are collecting more data and significantly investing in their MarTech and data capabilities, many brands are still struggling to get beyond the basics of customer personalisation. So, what can marketers do to help realise their personalisation ambitions and deliver growth for their brands?
MARKETERS, TAKE BACK CONTROL OF YOUR DATA
If data is the currency of personalisation, then as marketers we need to have a comprehensive overview of what customer data we collect, where it’s stored, and how it can be accessed. However, in my experience, most marketers only have a partial view of their data (often restricted to a single or small number of platforms).
There are multiple reasons for this, the proliferation of new platforms and repositories, the increased accountability and autonomy of technology departments and so on. My hunch is that as marketers we’ve also stopped asking questions of the data environment and have ceded control and, along with it, understanding. One of the simplest tools that I’ve used to overcome this is to plot a brand’s customer data ecosystem (from a marketing, not technology perspective). To take stock of the wealth of data collected, the locations of where these data are stored and the level of integration with other data repositories.
By plotting and understanding your brand’s customer data ecosystem you will unveil hidden insight about the depth and breadth of customer data you hold and the level to which it can be used to power behavioural targeting and personalisation. Additionally, by better understanding your data ecosystem you will be better informed across the following five areas:
Identifying what customer Personally Identifiable Information (PII) data is held where within the organisation and also what data is held by third-party platforms or partners will be hugely valuable. In an increasingly regulated and data-privacy compliant world, the benefit of understanding what data is held where cannot be understated. For example, often a key source of data that is overlooked is the repatriation of eDM behavioural data (sends, opens, clicks and opt-outs) held in third-party platforms back into a connected customer record or repository. Plotting your brand’s customer data will help uncover these sources and types of data and help to identify any potential privacy risks or considerations.
Many organisations create aspirational customer journeys, but how many of them are aligned to data and MarTech requirements? How many customer journey maps are presented and then are rolled up and stored in a poster tube? I know the power of visualising aspirational customer journeys and the benefit they can provide in terms of customer-centric thinking as well as a tool to showcase the vision for customer experiences. I also believe that these journeys deliver true value when aligned with data and MarTech requirements. By plotting and understanding the customer data landscape, marketers can create aspirational journeys and align these with current data (and MarTech) capabilities and identify the gaps and associated solutions to delivering these aspirational customer experiences.
Establishing what customer data is captured and held is essential to be able to understand how data can be used to power personalisation, but equally important is identifying what data is not captured, held or derived. Whether as an output of plotting customer journeys against data and tech requirements or as a standalone activity, identifying data and insight gaps is a key input in creating a data strategy that will help increase customer insight, understanding and action. Whilst many brands are either pivoting to first-party data or continuing to evolve their first-party data capabilities, by only focusing on the data that customers provide as they interact with your products and services limits your understanding of customers. Leading brands are blending different types of data to provide a holistic view of their customers and the market. Whether at an individual, household or geographic level, blending different types of data will deliver colour, completeness and context.
In today’s data-rich environment, a familiar challenge is the ability to transform data into actionable and accessible insights. Brands need data translators. Whether referred to as ‘translators’, ‘growth hackers’ or ‘data consultants’, there is an acknowledgement that due to the complexities of data coupled with basic levels of analytic and data science expertise in many marketing teams, there’s a growing tension between marketing teams and data science functions. As Hans Rosling once noted, analysts typically present statistics as notes, not music, but in my experience, marketing teams often don’t tell data scientists what music to play. Part of the reason for this is that often marketers don’t know the breadth and depth of data available to analyse and therefore analytic briefs often veer between a very narrow focus (based on a limited knowledge of what data is available) and open-ended briefs. Often based on a lack of understanding of what data is available across a broader horizon within the organisation. If marketers better understand what data is available, the scope and focus of analytic and data science briefs will be improved.
Many marketers complain that analytic or technical solutions are often delivered or provided to them, rather than co-created. This is a common (and increasing) trend and whilst the reasons (and solutions) are many and varied, without a clear understanding of what customer data exists (or is missing) and how this current state relates to the vision for customer experience, marketers run the risk of being end-users and not co-creators. Having a clear understanding of the customer data landscape alone will not suddenly transform internal development processes, but it will mean that marketers have an informed opinion and voice.
In a rapidly changing and evolving marketplace, the awareness and expectations of how customer data can deliver business growth is increasing rapidly. The media and C-suite now have a greater appreciation that customer data should be viewed as a ‘competitive asset’ – a unique view of your customers that your competitors can’t easily replicate. From a consumer perspective, we’re more aware of how valuable our data is and how it can be used to enhance our experiences with the brands and services we interact with. Marketers are responding to this challenge by continually seeking to take advantage of the increases in customer data volumes and MarTech capability to deliver ever more personalised and rewarding experiences.
The path to personalisation is long, but if data is the currency of personalisation, then the first step in the journey has to be understanding what customer data is available and how it can be used to deploy contextually relevant messages that increase customer volumes and value.
Head of Analytics and Insight