Digital transformation is more than having the right data, technology and people on your team — it’s about bringing them together

Lysianne Planche, Jamila Satani / March 2021

Lysianne Planche and Jamila Satani from Loblaw Digital’s marketing intelligence team share insights from their team’s digital transformation.

Customer expectations are at an all-time high. Marketing and product teams require information in real-time — results and analytics that can optimize advertising and personalization strategies, and deliver a better customer experience.

Last year’s acceleration of e-commerce has given marketers access to more digital data, feedback loops and insights than ever. But marketing intelligence isn’t just about having access to data. Marketers also need to understand the story behind the data, what lessons can be learned, and how they can be applied to create better customer experiences at scale.

Three years ago, we formed the Loblaw Digital Marketing Intelligence team. Our mandate was to bring our media buying activities in-house and supercharge our digital marketing efforts using the wealth of data available across our organization. We would take that data and marry it with the right technology platforms, then bring in skilled digital marketers to take our efforts to the next level.

Our team has unlocked new opportunities for better measurement, and demonstrated the value of digital marketing across our company.

3 illustrations represent steps towards digital transformation: Make marketing platforms part of the ecosystem. Have the right people & partners in place. Integrate your data & the processes to analyze it. Test and iterate internally, and in-market.

Make marketing platforms part of the ecosystem

When we began developing our strategy, we had to implement a marketing technology stack from scratch. For Loblaw Digital, this required bringing together analytics, demand generation and growth marketing teams, as well as data science and platforms, technology and legal and privacy.

It was a coordinated effort to evaluate the technology we already had with what was available on the market, and what would best suit our needs across the organization. We worked closely with our data and tech partners and completed the implementation and usage maturity assessment to identify any knowledge and training gaps within our teams. Without a solid understanding, teams may be looking for solutions that already exist.

One of our main criteria was the available integrations and connections between the platforms in our tech stack as well as our data environment. We integrated our marketing and data management platforms with Google Cloud, to enable an automated flow of data into one place. This created new opportunities for our marketing, media and analytics teams. It also allowed us to learn more about our customers and personalize their experiences across all of our channels in new ways.

Socialize the value you can enable for partners and identify champions within other teams who are keen to collaborate.

Have the right people and partners in place

As we worked through implementation of our marketing tech stack, we needed the right people on our team. We looked for marketers with a mix of tech experiences, as well as experience with data, analytics, and insights.

Once our team was in place, we did an internal roadshow to learn about capabilities amongst teams and let them know what we could offer. Instead of working in silos, we brought the data teams right into our meetings and conversations and came to them with specific requests.

It’s important to socialize the value you can enable for partners and identify champions within other teams who are keen to collaborate. This also helped us establish credibility within the organization.

Integrate your data and the processes to analyze it

In many organizations, data is spread out across ad campaigns, CRM systems, websites and apps, loyalty programs and more. We created processes to break down organizational silos and automatically capture as much data as we could in one place. And in doing so, saved roughly 16 hours a week from manual data download, model re-running/scoring, and uploading for remarketing lists.

To do this, we brought disparate data sources into Google Cloud, but getting there was a journey. It required figuring out who were the right people to support us, how to best store the data, and how to access it with the right permissions. Our team then had to do extensive work to organize it, validate it and massage it to provide marketing insights.

We started small, with a couple of use cases that could prove value right off the bat. We were spending a significant chunk of our media budget on site retargeting and saw an opportunity to use our data platform and cloud infrastructure to enrich site data and spend more efficiently. After getting buy-in from our stakeholders and media buying partner teams, we started building a propensity model for one of our businesses, to help predict consumer behaviour.

Test and iterate internally, and in-market

Once we had the model up and running, we worked closely with the teams to generate hypotheses on how we could target and measure. We had many questions. Does retargeting really drive incremental sales or would these people have purchased anyway? How do we know which deciles and targeting messages would drive the most bang for our buck? We then worked with our creative teams to build out a variety of creative options. This was challenging, as we had to work cross-functionally with many different teams.

Being able to run this entire data-driven proof of concept and measure its performance — all within our own team — was a huge win.

After running the first test in-market, we were able to iterate and validate our assumptions. One of the most interesting insights that came up was that the incremental value of remarketing was most important to “warm” customers in the funnel. This learning allowed us to shift these customers into our highest propensity-to-convert bucket. Being able to run this entire data-driven proof of concept and measure its performance — all within our own team — was a huge win.

These days, our focus is on customer experience, personalization, automating and executing efficient campaigns, making sure we’re making the most out of our media dollars, and delivering strong results while reducing budget waste.

We’ve come a long way over the past few years but we’re still on our journey. We’ve learned that true marketing intelligence is not just about having the best data, the best technology or the best people on your team — it’s about bringing them together. Doing so can position the entire organization to be ready to adapt to industry changes that may come.

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