Too much customer data not enough insights
By Elisa Adams, CEO of Sprout.
Today we are very fortunate. Customer data and feedback is everywhere! There’re a gazillion tools to help you collect it, summarise it and report on it. What is lacking, however, is the ability of most business leaders to leverage this data to make sound strategic decisions, which lead to growth.
I know this is not new news to many. In fact, as highlighted by the 2021 GRIT Business and Innovation Report, our clients have clear priorities when it comes to what they need to achieve from investment in data and insights. The top priorities are:
- Providing results executives can act on
- Being able to make impactful recommendations
Both of these priorities require commercial, actionable insights, not just a lot of data. This problem stretches across all stakeholders. According to research from Forrester few brands do CX well. The major problem? For most organisations it is their inability to draw meaningful insights from the data they have about their customers.
Most business leaders and marketing executives understand the need to be data-driven and its importance in driving personalised customer experiences. Where they fail is in their ability to act on the customer data they collect. According to a survey conducted by Oracle 93% of executives in global enterprises believe they are losing 14% of annual revenue due to not being able to act on their customer data.
Customer data is only useful if it can be linked together to reveal insights. I know this word is overused and under-understood. But at its most rudimental, an insight should tell a story that reveals or identifies something that the business can act on. Insights lead to actions.
The roadblocks to meaningful and useful insights
Organisations face significant challenges when trying to leverage their data. The first challenge is the amount of data they collect and the variety of sources it comes from. Mark Albert, chief data and analytics officer at Ogilvy Australia, comments, “The first challenge is ensuring that data collection, and the right data collection, is a priority for the brand. It’s important to focus on those potential initiatives that will maximise brand impact – there’s always a danger of focusing analytics efforts in the wrong areas or being guilty of analysis paralysis!”
It’s a monumental task that requires considerable planning to decide what needs to be done, how it’s to be done and when it needs to be done by. Either way most companies have LOTS of data.
As well as the challenge of managing large volumes of data other factors come into play to make the job more difficult. “Broken data flows and an inability to fuse data sources can make it harder to derive valuable insights from the data that the brand has collected”, says Albert. “Additionally, failing to identify the analytics resources and tools required for the specific task at hand and the metrics necessary to gauge performance can hinder the quality of data analysis”.
At every touchpoint along the customer journey, the customer is likely to be interacting with multiple systems[i]. At one touchpoint they are having a marketing experience at another it could be a product experience or service experience. Each touchpoint is generating its own set of data and building its own segmented view of the customer, creating data silos across the organisation. Disjointed and siloed data leads to poor visibility into customer trends and, therefore, flawed strategic decisions. Research from Dun and Bradstreet highlights that 80% of companies struggle with issues surrounding data silos. Organising and streamlining the data is a critical step in making the data ready for insight development.
Possibly the biggest challenge, however, is the ability of those responsible for collecting and analysing data to communicate insights among business stakeholders. “If the data strategists or customer insights people are unable to contextualise the findings, and highlight the relevance to broader business objectives, then traction is less likely, which in turn, weakens the value of data to drive brand impact”, says Albert. This is the ability to translate data and insights into actionable pathways. We call this ‘tripping at the finishing line’ – the inability to provide results that stakeholders can act on.
Recent research by Sprout Strategy confirms this as a challenge for insights and research teams. A pain point for the data strategists or customer insights people is gaining the the full support of their senior executives and demonstrating the value they contribute to the business.
To deliver the full value locked inside these teams, they need data that explains what is happening and WHY it is happening. The WHY unlocks insights. Combining internal data and behavioural data with primary research allows business to develop insights that can achieve real business goals such as improving customer lifetime value, reducing customer churn or generating sales growth.
Build a strategic insights roadmap
For brands to leverage their data and generate insights that have beneficial impacts for the business, they must break down their data silos creating a single and connected view of the customer. The first step in creating this unified view of the customer is to build a strategic insights roadmap.
A strategic data road map helps you identify the data that will provide the most value in achieving your brand, CX , and business goals. It also helps you to identify what you will need in terms of people, processes, and technology. Albert comments, “It’s important to remember that one brand’s ‘useful data’ could well be another brand’s ‘useless data.’ To gain the most value from data collected, brands need to have a clearly articulated strategic insights roadmap in place that is aligned with both the marketing strategy and broader business objectives”.
In building your roadmap Albert recommends that you involve key business stakeholders early in the process. Establishing a clear understanding of stakeholder needs and the problems they are trying to solve helps obtain ‘buy in’ and identity what insights need to be generated. Engage stakeholders to understand their roles, objectives and the ways in which they work to determine what’s important and how the insights generated can best support them.
Albert advises, “It is also vital to contextualise the purpose and commercial application of the data that a brand collects so that its value is understood across the organisation. This way, leaders and executives will be able to use the data and the insights it generated to bring about gains for the wider business.”
“Additionally, if a brand is beginning its data journey, or is struggling to filter out the useful data from that which is just noise, I would advise to review all current data and insights projects, push pause on those that are currently non-revenue generating and focus on those data projects that do drive brand performance”.
Hire a customer data and insights team with the right skillsets
You need the right team and the right people with the right skills to enact your roadmap. According to research from the Boston Consulting Group, 75% of CEOs believe that a high performing customer insights team was essential for accelerating business growth.
Finding and hiring people with the right skillsets to join your insight team, however, is a significant challenge, as Albert points out, “Data is a broad subject, and there isn’t a one size fits all approach to team structure or how this is managed within a company. Inevitably, this variability can cause issues when working out the most appropriate combination of data skill sets for your company. For example, it is easy to fall into the trap of employing “the data guy”, only to realise that a data engineer has been employed, when really what they needed was a data strategist – or vice-versa”.
As the amount and type of data proliferates, the range of tools and skills required to manage and analyse are constantly evolving. “By understanding the various data and insights disciplines that are needed to support business requirements, and then working with trusted partners or developing data talent internally, the appropriate team can be established, which will deliver the best data insights. This will ensure that measurable business goals are achieved”.
Avoid a technology led approach
Too many make the mistake of starting their data journey with a technology led approach. It’s easy to get excited by deploying the latest and best technology, thinking that this will solve all the challenges.
Don’t get me wrong, Artificial Intelligence (AI) and machine learning are powerful tools for analysing data, but as Albert advises, “The extent to which AI and machine learning can help will vary according to each brand’s sophistication in data analytics. In the right hands, and with the right application, these tools can be very powerful.”
Your starting point for leveraging data for growth, should be your business objectives. Clearly understand how your data and insights strategy will support your organisation achieve its business goals. You need a clear and articulated vision of how your data and the insights generated from that data will deliver value to your business and your customers. Whether you are starting your data and insights journey or have been doing it for years, it is always good time to check in on your strategic insights roadmap.
If you need help building your strategic insights roadmap you can contact Elisa@sproutstrategy.com.au. Alternatively Sprout can audit your existing data insights strategy to ensure your organisation has a fit-for-purpose and best-practice customer insights program.