On 24 September 2020 BIMA hosted a roundtable session under Chatham House rules which aimed to explore the key blockers brands face in pursuit of digital transformation and delivering better digital experiences. Held in collaboration with Acquia, the session specifically focused on exploring – and overcoming – barriers concerning data.
Paul Moss, Chair of the BIMA Data Council, hosted and co-moderated with Eric Fullerton, Lead Product Evangelist at Acquia. They were joined by attendees from a variety of roles and backgrounds including director-level, data, strategy, AI and UX.
COVID has led to a huge acceleration of digital transformation, making it more critical than ever to similarly accelerate the transformation of data. Channel proliferation can slow data transformation down, creating data siloes which lead to disconnected systems. Brands need an agile customer- and data-first approach to ensure they can rapidly shift towards strong omnichannel and customer-led experiences and engagement.
The roundtable agreed that big digital transformation projects often struggle due to a lack of appreciation of the overall change they bring to the business. There’s a need for businesses to appreciate that new digital technology also brings a change for people and processes. This needs to be planned for. Many at the roundtable had seen brands investing in and being seduced by the promises of a new tech stack whilst underinvesting in essential elements beyond the technology itself, e.g. strategy, content, creative, data.
But it wasn’t just about an underinvestment issue. Attendees also felt that, in pursuit of digital transformation, brands were not setting clear and realistic business objectives against their transformation vision. Often, the desire was to ‘go for gold’ and expect magic to happen through the procurement of technology. Roadmaps often reached for a single silver bullet instead of including quick wins and building multiple iterations of incremental value.
There was little evidence of bringing test and learn and innovative experimentation into the roadmap, so many months into the project there was often nothing to show. There was a lack of understanding of what was working and what wasn’t. Chasing the ‘big dream’ tended to mean focusing on bigger, outcome-orientated KPIs with less consideration of measures that drive success and shift those outcomes.
Everyone at the roundtable agreed that companies are becoming more aware of the importance of data. But attendees also agreed that data is a discipline that can be very hard to understand. As a result, a digital transformation may end up having a narrow or over-simplified data strategy – or lack a data strategy altogether.
Data is often linked to a very specific objective, such as personalisation and enablement of relevant content, which can remove it from having a central role in the broader strategy.
The complexity and perceived difficulty of data also result in a tendency to look for easier questions to answer, leading to lazier ‘get the system to do that’ responses. Data strategy requires much more detail than that.
Some felt data was more likely to be taken seriously when there was a business-wide focus on customer-centricity. If customer-marketing has more respect within a business, then the data strategy often has a much greater elevation – all the way to board level.
Some agencies noted that the need for a data strategy was better amplified when they emphasised the cross-functional purposes and benefits data provides. Agencies’ data skills can be put to greater use beyond the pure ‘marketing’ decisions they historically focus on. With the right data access, agencies’ strategic and technical data skills can benefit areas such as operations or product development. Access is a challenge, however. Data regulations such as GDPR, understandably mean that brands have become extremely cautious about external parties accessing, processing and analysing their data. This limits the ability of the agency to prove its value. However, agencies felt that brands able to overcome these barriers create more successful, more innovative agency partnerships.
The session identified several recommendations:
Look beyond a technology change
Greater success will come from collaboration between technology vendors, suppliers, agencies and brands; all working together to avoid a transformation project becoming associated with ‘bad tech selling’. Brands need to think about the investment outside of the tech, such as people and processes – as well as key enablers such as data.
Use specialist skills in content, creative and data strategy
Agencies or specific consultants can sometimes be excluded from projects that are perceived to be heavy-lifting tech projects. These people are as involved – if not more involved – in creating and activating marketing strategy and digital plans as the brands themselves. Agencies can also rapidly plug gaps in digital transformations – especially when the agencies have strong data credentials.
Set business objectives and audit the situation
Objectives need to be clear, realistic and measurable, and include a data audit upfront. An understanding of the current data landscape, beyond the usual personal and transactional data, is necessary. This enables the identification of critical data gaps and requirements against the business objectives, which then feeds into the data strategy.
Ultimately, digital activity needs to be linked to success so we need to build foundations that enable and prove that success. And we need to focus on the drivers of a successful outcome, not just on the outcome metric.
Create a data strategy
Having a data strategy, plan or roadmap is essential. Setting time aside to take the organisation through the digital and data transformation will help with executive buy-in and enable the workforce to understand what they will do differently. Once the plan is in place, continue to take people on that journey.
Experiment and learn – don’t expect a silver bullet
Prove little things along the way. Don’t ‘go for gold’ without having a range of hypotheses that can be tested and used incrementally to create longer-term value. Learn from failures.
Take customer-centricity more seriously
Customers are demanding more convenience and relevance at every touchpoint. To service their customers, brands should re-examine their business model to ensure their data-first approach goes hand-in-hand with customer-centricity.
For anyone beginning their data journey, a customer-value framework is a recommended starting point for defining how brands will deliver value to their customers and themselves. Alongside this, brands should understand the data model they currently have and work out which elements are vital.
Building first-party identifiable data is typically a key part of the customer-marketing plan. Collect as many customer attributes as you can and gain permission to process this data and engage with them. Don’t just use the data to segment customers and drive engagement – the data collected is a rich source of customer insight and can be used to quantify the value created.
Finally, the roundtable acknowledged that data is hard! But that doesn’t mean a data strategy should be avoided. New digital technology won’t get off the ground without organising the existing data estate and having a plan to bring new, essential and accurate data into it. The right blend of experts from tech partners, suppliers, agencies and the brand itself is capable of achieving this.
In partnership with Acquia
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