This narrow scope is not only frustrating for commercially-minded practitioners, it also prevents the business from creating the data-driven services and experiences needed to positively reshape the customer relationship. Barriers exist in the form of traditionalist business stakeholders, who are often more inclined to make decisions based on their own experience-led assumptions rather than data-driven insights. The data team itself can also suffer from a lack of commercial awareness, preventing practitioners from landing insights in a digestible and actionable format.
At a DataIQ Leaders roundtable in October 2021, members discussed the best methods for aligning data and analytics with business stakeholders and their processes to reshape the customer relationship. The conversation focused on the need to establish a clear view of the consumer, both within the data department and throughout the wider business, as well as the importance of tailoring insights to complement established business practices.
Who are your customers?
With a majority of businesses undertaking a wholesale change to be customer-first, it follows that organisations, and the data teams within them, need to comprehensively understand those customers.
The pandemic has clouded this view, with shifting markets making customers harder to identify. According to research conducted by DataIQ, the use of internal customer data has expanded within 51% of organisations since the outbreak of the pandemic. Moreover, customer intelligence data saw the highest level of increased demand during the pandemic, followed by demand forecasting and customer segmentation.
In order for data to inform customer-centric business strategies, the data department needs to have a clear view of who they are targeting and how granular customer-led insights should be. This is no easy task, particularly within large, disparate organisations with competing priorities.
One member from the legal sector said: “If you’re part of the business services function, then your customers are the partners and the lawyers. For partners, their client is the end user. Its vitally important that the data department breaks this down to get an understanding of the different views of the consumer across the business so that we can tailor insights to suit those very different conversations.”
A similar dynamic exists within one member’s educational organisation. “We’re constantly looking to make data-driven interventions in order to improve the student journey,” said the member. “This is particularly difficult for us, because the definition of ‘student’ is broad and encompasses a range of competing needs. Understanding the demographics of the customer base is key.”
Aligning with the business
A criticism often landed on data professionals is that they lack commercial awareness. In organisations where data sits as an adjacent unit to those involved in decision-making, this can lead to a dynamic where decisions are made off the back of assumptions rather than insight – even when individuals are genuinely customer-focused.
There can be a temptation to position gut feeling as the antithesis of data-driven decision-making. However, gut feelings are often informed by years of experience and an exceptional knowledge of the client base. Data should complement this knowledge, not overwrite it. By taking the time to understand the business and the working habits of key stakeholders, data practitioners can establish the trust and confidence required to embed data within customer-focused decision-making.
One roundtable attendee from the telecommunications sector said: “Particularly within retail, people know their client base. Its up to data teams to sit down with the business to work out whether a new dataset or model will fit into the existing way of working.”
By tailoring models to help with specific interventions, rather than ripping up the rulebook, data teams can avoid stoking fears that new models and processes are being built for the sake of job replacement. “This may lead to a situation where your model isn’t providing the business with much additional information,” said one member. “But by making incremental improvements to efficiency, you can take the baby steps that are so important for building trust. You’ll then move up the food chain and data will be invited into more conversations from the outset.”
Establishing effective channels of communication is essential for any data team looking to ensure that the business takes insights on board. This has been a long-standing challenge, with technical capabilities within the data department often mirrored by shortfalls in the ability to visualise and report on findings.
Data teams have adopted a plethora of methods to help overcome this hurdle. At last month’s DataIQ Awards ceremony, the Superdrug Insight team won in the most effective stakeholder engagement category thanks to its innovative insights champion programme. The programme enlists colleagues from various business functions to serve as vocal advocates for data and insight – engaging in monthly catch-up meetings in which the data team showcase new ideas, tools and insights.
One roundtable attendee added that their team sends a monthly newsletter to the business, providing updates on the projects the data team is working on and opportunities for collaboration with various business units. Another member organisation holds regular virtual sessions in which junior members of the data office highlight market insight and new products to a commercial audience.
“We don’t focus on the underlying datasets themselves, because the business, frankly, doesn’t care about that,” said one member. “We focus on how we have or potentially could answer questions around how we market and range products.”
Data-driven or insight-driven?
It can be helpful to consider terminology and messaging when debating conceptual topics such as strategy and business management. It is in vogue for decision makers to profess to be data-driven, despite often failing to know what that means in practise. When the data team fails to guide the data-driven approach, businesses run the risk of decision makers coming to well-intentioned but ultimately harmful conclusions under the pretence of being “data-driven”.
This was the case for one roundtable attendee, who leads a data and analytics function for a large telecommunications provider. After being encouraged to use data to inform interactions with customers, the business circumvented the data team to access data provided by client routers. They then reached out to customers identified as having below-average broadband speeds, many of whom hadn’t realised they had an issue in the first place – leading to a slew of unnecessary complaints and cancellations. “In big organisations you have to ensure that data is being used at its best both for the customer and the organisation,” said the member. “Your business might be data-driven, but it can still be doing the wrong thing with it.”
Providing the business with access to data won’t necessarily lead to useful data-driven decisions unless they are properly guided. One roundtable attendee used the analogy of a set of golf clubs: just because you’re using the same set as Tiger Woods doesn’t mean you’ll be as good as him on the fairway. It is perhaps more helpful to consider how best to import insights, rather than data more broadly, into customer-centric business strategies.
Once solid data foundations have been established, practitioners should then work to understand where data can be applied and the level of insight needed to facilitate it. Insights should be tailored to maximise the chances of influencing decision-making, which in turn will minimise the risk of data being misinterpreted and applied in the wrong context. As one member said: “Rather than dumping data onto the business, the team should consider what is the individual decision they’re influencing and at what granularity it can be applied.”
Key takeaways:
- Understand your customers. Data struggles to support customer-centric business strategies when the view of the customer is unclear. Working with the business to understand different views of the consumer can enable practitioners to tailor insights to suit different conversations.
- Work with the business. Data should complement existing experience and knowledge of the client base within the business, not overwrite it.
- Be insight-driven. Just because the business is using data doesn’t necessarily mean it’s using it well. By generating understandable and actionable insights, the data-team can ensure that data effectively steers customer-centric strategy.
