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As chief marketer at SAS, Adele Sweetwood knows more than a thing or two about leveraging data analytics to market her company’s analytics software to organisations.
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After all, SAS, like most technology companies, eats its own dogfood – by using the same marketing analytics tools it sells to make sense of the vast volumes of data being generated by people who interact with its brand on a multitude of digital channels across multiple devices.
Although Sweetwood would certainly not need to convince the company’s management about the benefits of marketing analytics tools, she faces a different set of challenges in delivering on the promises of the technology.
“At SAS, we’re lucky because we have technology options, but just because you can deliver the technology to marketers doesn’t mean they will turn into analytical marketers,” says Sweetwood, the company’s senior vice-president for global marketing.
“You’ll have to change the mindset and culture of the organisation, align values and objectives and focus on making data-driven decisions,” she says. “You have to do all that without eliminating the value of the creative side of marketing.”
Marketing analytics tools from the likes of SAS, Adobe and others have been available for some time now. The demand for such tools has grown as marketers compete to deliver personal and contextual customer experiences while measuring the impact of their marketing investments.
The same tools can also be used to ascertain if a piece of creative work is resonating with audiences, Sweetwood says. “The look, feel and emotion are still important components of marketing, but now we have data to tell us whether something is working or not.”
Indeed, rather than oppose the use of technology and data, creative types at SAS have lapped up on the insights gleaned from the company’s data analytics tools. “For the most part, people took it as an opportunity to try different things – it has created a testing culture that adds value to the marketing process,” she says.
The bigger challenge, says Sweetwood, was in getting the company’s marketers to change their mindset of focusing on products, messaging and marketing channels, to one that puts customer behaviour and preferences first so that they can deliver good customer experiences.
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“Marketers need to realise that they get better results with a targeted, more analytical approach, and we do that not by forcing a report or process on them, but by using data to show them the impact of their work,” she adds.
Sweetwood also points out the importance of having an organisational structure that promotes a data-driven, collaborative and interdependent culture – one where digital, search and data visualisation teams are aligned with a company’s go-to-market team, for example.
“It’s not one group telling another about what’s right or wrong – it’s how they look at things together,” she says, adding that while there may be some initial resistance, marketers will eventually need to improve their skills to remain relevant in a world where customers are calling the shots.
To ensure marketers at SAS have the skills they need to succeed, Sweetwood says the company spends a lot of time disrupting job functions, as well as drawing up learning and development plans.
“There’s also a mixture of hiring when there’s a gap, upskilling those who show an interest in a particular role and broad-based certification for everyone,” she adds.
Drawing from her experience in driving the use of data analytics at SAS, Sweetwood says organisations should also make a clear distinction between reporting and analytics.
While reporting is largely about communicating key performance indicators, Sweetwood says analytics is more about analysing why a marketing campaign is not working as well as it should, for example.
Ensuring that employees are accountable for their data is just as important, Sweetwood says. “Traditionally, marketers like to say the data is wrong, but my answer to them is: didn’t you contribute to that data?”
To that, Sweetwood advises organisations to establish a single source of information with data definitions, metadata and business rules that are agreed on by everyone.
“That’s not going to be easy for every organisation, but we did it by partnering with IT to develop a data warehouse structure,” she says.