Barilla’s VP Data & Analytics: ‘at the end of the day, we want to get more people to enjoy our brilliant pasta’

In marketing, and in business more generally, we often hear that decision-making should be “data-driven”.

Data can yield all kinds of crucial insights into customer behaviour and preferences, as well as helping to identify opportunities, potential challenges, and strategies that are working effectively. Driving decisions with data therefore sounds like a solid way to succeed in a world with more data present than ever before. However, Lyndsay Weir, VP Data and Advanced Analytics at Italian family-owned food company Barilla, says that what your decision-making should really be is people-driven.

“The data can help fuel it, but for me – yes, data can provide decisions, but we need to know why we’re doing that, and to shape it and do it for the right reasons,” she told attendees at Econsultancy Live: CX 2022. “Within Barilla, we’re of course going to be using data to do this, but we need to be more people-driven, consumer-driven – because at the end of the day, we want to get more people to enjoy our brilliant pasta!”

Weir emphasised the importance of approaching data with a clear strategy for success, and orienting data work around consumer desires. “Even though we’re a data team, what we’re trying to do is transform the way we communicate with people,” she explained. “It’s why everything we do … is actually driven and enabled by what the consumer wants from us.”

Weir outlined three key components of a people-driven approach to data: use cases, quality data, and technology.

1) Use cases

“At the end of the day, any work our data teams do within Barilla – and any work your organisation should be doing with data – should come from the people who are interacting with your end users,” said Weir. And every kind of data point – from website visitors to product purchases to event sign-ups – needs to begin with a use case: a clear view on how the business is going to use the data you’re providing.

Weir recommended mapping out potential use cases along the consumer journey from awareness through to consideration, purchase, service, and loyalty expansion. For example, a use case in the ‘awareness’ stage might be improving the consumer search experience, using analytics or natural language processing to understand how consumers are using search and what they might be trying to find. In the ‘purchase’ stage, digital shelf analytics could help with product optimisation – pricing, promotions, or ratings – while consumer engagement scoring could improve customer loyalty in the ‘loyalty expansion’ stage.

“There’s so many different ways you can use data and analytics along the consumer journey,” Weir said. “For me, it’s about where you’re wanting to engage the most on that consumer experience and making sure it aligns with what you’re trying to deliver.”

To that end, Weir also advised prioritising the most valuable use cases and data opportunities; while there might be hundreds of possible opportunities to use data to optimise aspects of the consumer journey, not all of them will be worthwhile or actionable. She recommended asking the following questions to determine value:

• Can we do it?
• Do we have the team to do it?
• Is it going to drive us gain?
• Can we do it quickly?

Barilla’s data team uses a proof of concept cycle to determine which solution is worth putting its collective energies into. “We want to test it; we want to see if it works; and as a global organisation, we need to pilot it with a certain market or region first, before taking it out to that huge beast that is a multinational CPG,” Weir explained.

The team adopts a ‘test and learn’ and ‘it’s fine to fail’ mentality throughout this process. “We’ve got our use case; we know what we’re trying to test, and at the end of the day, what we’re trying to improve for the consumer; and then we take that through an eight- to twelve-week cycle to bring it to life at small scale at first. If it works, we can then scale that, embed it, and drive it across the business.”

She also emphasised that investment is key: in people, in understanding, in tools, in feedback, and in quality measurement. “It’s important to get it right every step of the way if you’re going to improve your consumer journey.”

2) Quality data

Obviously, none of this is possible to do without data; but many organisations, Weir said, wonder how they can get hold of the data they need in order to achieve what they want. Her advice was to “start being brilliant at the basics”.

“Look at what you’ve already got, as an organisation, and look at how you can bring that into one place to democratise that data, clean it up, and allow people to have access to it, to start asking, ‘So what?’”

Getting access to quality data also comes back, once again to putting the consumer front of mind: why should they give you their data? “These days, it’s really rare for people to want to give over their email address for no reason,” said Weir.

“You’re going to have to be a privacy-first organisation; they need to trust that the way you store [the data] is secure; and also, you need some good value exchanges.”

Weir’s mantra around data is: “have less, but do better”. Many organisations try to aim for the “big data” approach, but without a clear use for the data, and with much of it being collected using outdated methods. Weir emphasised the importance of having a centralised storage point, with a clear way to access it, and no silos. Data also needs clear foundations – such as taxonomies, or a catalogue of data sources to easily identify what data you have and where – to enable better CX and growth.

“Do you have a data catalogue to say, ‘We’ve got data on this consumer; it tells us these shopping preferences, or these dietary requirements’? Do you know that about your business to date? Would you know what information you’ve got and what you can use to drive a better consumer journey?” asked Weir.

3) Technology

“It’s really paramount that if you want to have a better consumer experience, if you want to do data and analytics on the consumer, you’re going to need a piece of technology that brings all that consumer data together into one place, to that single consumer view,” said Weir.

Without wanting to delve too deeply into the pros and cons of specific technology platforms, Weir said that finding the right piece of martech is about “understanding ‘What’s your use case? How do you want to talk to your consumer?’ And what can you bring together to get your outcomes?”

When it comes to data tools, it’s also important not to get so hung up on things like visualisations that you forget about what Weir calls the “So what?”: understanding and acting on what the data shows. Weir reflected that a lot of companies “can talk business, but they can’t talk data – and they don’t really know how to turn that data into actions”.

“It’s the biggest pitfall when it comes to taking [data] to the next level: we spend so much time on that visualisation, or the great dashboard or the great tool – but so little time investing in the ‘So what?’ and the ‘What’s next?’” she said.

For Weir, three key things are needed to make this happen within an organisation.

Capabilities and comms

“There’s a lot of opportunities for the consumer experience if we’ve got the right people and capability to unlock that within our organisation,” said Weir. She advised looking at where you want to be in five years’ time, then mapping the people and the data skills your organisation has currently, and using this to build a robust training plan and internal capabilities programme.

Weir also spoke about the importance of bringing everyone with you on the data journey by democratising access to data and opening up tools. “I had a great CMO in a previous organisation who was hands-on working with me in Data Studio dashboards to build out reports he wanted to see himself – because he wanted to know what to do and how to unlock it,” she said. “And I think that’s really crucial.”

Bringing people along with you on the journey also means sharing successes and proofs of concept across all levels of the business, creating things like videos or one-pagers to help people understand what is being achieved, how, and why.

Changing mindsets and working

‘No more silos’ is a goal for almost every organisation, but when building an organisational data culture, Weir particularly emphasised the need to collaborate across teams and understand what data would help them to accomplish their goals. “We might define what we’re working on, but we need to work with so many stakeholders at the same time – because at the end of the day, we need to involve those people who speak and touch with the consumers every single day.

“Whether that’s our shopper marketing team; our sales team; our ecommerce leads – they’re the ones who should really be telling us what to do, and we can then churn out the insights or models to make that happen.”

Similarly, Weir explained that the data team should bridge between marketing and IT – “because building that data culture is about sometimes the technical, and sometimes the bringing it to life, and we like to drive that together at the same time.”

Embedding into the organisation (or: apply your data!)

For all that proofs of concept are useful, Weir cautions against getting so bogged down in a proof-of-concept cycle that you neglect to action and scale the insights that work. “You’re never going to improve something for your end user if all you’re ever doing is small-scale test-and-learns,” she said.

“Of course, have a small portion of your business always bringing in the new – but don’t ever forget that the new you brought in now has the potential to really change the way your company operates for huge amounts of people if you do it in the right way.”

She also advised making use of the workflows and processes that already exist rather than trying to invent new ones from scratch. “We like to look at what’s already there – whether it’s brand planning cycles that have existed for years, or whether it’s a brand building capabilities tool. We want to fit into that, but with data along the way – so we can help people learn how to adopt it a bit better.”

Lastly, having an established KPI (key performance indicator) framework is crucial for measuring what you’re doing and getting feedback from people along the way. “If you’re doing all of this, make sure you’re measuring what matters,” said Weir. “Understand what you’re driving towards, and what’s your business objective. [Everything] should be driving towards this North Star metric – whether it’s increase in sales, share of voice, or at the end of the day, just a happy sentiment from the consumer.”