Connecting Siloed Data Biggest Challenge Say 65% Marketers: Deloitte Report
The Chief Marketing Officer (CMO) Council in collaboration with Deloitte Digital, the experience consultancy, published a new report, Data-Driven Decisioning Powers CX Forward. The new report details the challenges and best practices for defining and progressing toward an ideal customer experience (CX). The insights are based on two surveys of over 300 marketing leaders across […]
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The Chief Marketing Officer (CMO) Council in collaboration with Deloitte Digital, the experience consultancy, published a new report, Data-Driven Decisioning Powers CX Forward. The new report details the challenges and best practices for defining and progressing toward an ideal customer experience (CX).
The insights are based on two surveys of over 300 marketing leaders across a wide range of industries. The report highlights the time horizon to ideal CX and AI, operational and advanced data capabilities, the importance of a customer data platform, and overcoming a skills shortage.
Ideal CX is about tailoring a message to a customer in a way that moves the customer down the funnel and toward a transaction, whether that’s a sales conversion or an information exchange, with as little friction as possible. Further, ideal data science/AI/ML capabilities provide CX with enough data to make informed decisions around what to do next, i.e., the next best action or next best offer.
Opportunities for improvement
- 69 per cent of marketing leaders are still developing or defining their CX strategy
- 40 per cent believe it will take well over a year to deliver ideal CX
- 14 per cent say ideal data science/AI/ML capabilities are more than 18 months away
- 65 per cent agree connecting siloed data/content is the biggest challenge
“Much is on the line, given the transformative powers of using data and AI to create richer CX,” said Donovan Neale-May, Executive Director of the CMO Council. “In order to achieve such a competitive advantage, our study points to the need for more and better: more data, better data, more technology, and better technology, along with data governance and data analytics.”
Top five challenges
- Connecting siloed data and content from multiple systems
- Creating cross-channel customer experiences
- Having the right skill sets in place internally
- Having an incomplete view of the customer
- Having poor alignment/collaboration across teams
Also Read: How Location Analysis Helps Data-driven Marketers
Introducing ideal AI
What does ideal AI look like? AI supercharges CX with speed, scale, prediction and learning. The ideal AI capability provides CX with enough data to make informed decisions around what to do next, i.e., the next-best action or next-best offer.
As a customer enters into a consideration set, for instance, ideal AI gives marketers choices on how to interact and then learns from the outcomes. It’s reaching out ahead of the right time by predicting what customers will do, taking relevant actions, and ultimately giving customers a better experience.
Yet many challenges await marketers wanting to implement data science/AI/machine learning capabilities. Chief among them: hiring more talent with AI skills, partnering with IT, cross-training existing talent, choosing the right AI technology, and proving the business value of AI.
Also Read: Holiday Retail Sales Expected to Increase: Deloitte
CX-related Data Capabilities
When it comes to CX-related data capabilities, the study identified two categories: operational and advanced. Marketing leaders can gauge how far along they are in the race to ideal CX based on the maturity of these data capabilities.
Operational capabilities span customer data management and governance, operational reporting, guided analysis, performance visibility, and ongoing insights generation. Among marketers, 15-20 per cent think their operational capabilities are “developing,” 35-40 per cent think they’re “defined,” 30-35 per cent think they’re “advanced,” and 10 per cent think they’re “best in class”.
On the other side of the spectrum, advanced data capabilities are nascent for most. These capabilities include scenario trade-off simulations, predictive modeling/optimisation, data science/AI/machine learning, and robotic/cognitive automation. They’re still in the early development stages, if they’re happening at all. In fact, 37 per cent of marketers who currently lack data science/AI/machine learning capabilities don’t even plan to build them.
“The days of personalisation as a ‘nice to have’ are long gone. Today’s customer expects that the brands they do business with are invested enough to serve them in a way that is efficient, transparent and unique only to them,” commented Michelle McGuire, Principal, Deloitte Consulting LLP and National Market Offering Leader – Experience Management at Deloitte Digital. “Our research found that many brands are still lagging behind in implementing the AI needed to create the immaculate, branded CX their customers demand. Our hope is that this report can help CMOs and organizations still teetering on the edge of embracing this technology see how it can provide them with the tools needed to achieve ideal CX.”
