Data is becoming the oil of consumer marketing

Allan Swart © 123RF.com

We've gone from the technology revolution to the information revolution. When we had the technology revolution it was all about owned, earned, shared and paid. Now with the information revolution, the media landscape is no longer linear. In the information revolution, each of us now leave a digital fingerprint, an infinite stream of phone records, texts, browser histories, GPS data and other information. This is what's going to stay behind. This is your legacy. This tells marketers who you are as a person, what you enjoy, what you like.

More data has been created in the past two years than in the entire previous history of the human race. That means data is becoming the oil of marketing today. But this is crude oil. “If you're going to put that oil into a car today, it's not going to take you anywhere. You have to refine it. And that's the challenge that we're all facing today,” says Less. But how do we refine the data?

The external challenge is that we have this exploding complexity. Mitchell Kapor, founder of Second Life said,

"Using information from the internet is like drinking water from a fire hydrant."

Leana Less © Twitter

What do you do with your data to make your business smarter? The first thing you do is to figure out if everything everyone is selling us is actually working for your organisation. That is how agile marketing works. “...we did a vendor study during the period from September 2014 - August 2015. It was very comprehensive. We included 203 brands, 120 countries and amongst ourselves we had about $16bn. It was a robust enough sample base for us to get some variants. We worked together with McKinsey & Company and Forrester on this study and found the business results were profound,” Less tells us.

Results of vendor study included:

• 1% higher profits if your organisation invested in getting a stronger analytics internal team - when you boost marketing analytics "units"/usage by 3 points (on a scale of 1-7)
• A company that uses data and actively reallocates spend based on data delivers, on average, a 10% return to shareholders, versus 6% for a sluggish reallocator. Within 20 years, the dynamic reallocator will be worth twice as much as its less agile counterpart.
• 12.7% lift in ROI on average across 11 companies committed to agile measurement and rapid reallocation.

“We had the business case to take to the business to say we have to make some changes. So now, for us we needed to change our model completely because the lines had become so blurred. The lines between content, connections, even our commerce teams," says Less. And that's hard because what they were trying to achieve was this:

"A family is like a forest, when you are outside, it is dense. When you are inside you see each tree has its place."

Tools

Challenge: Becoming a data-driven team encompasses more than just building tools and investing in technology. In order to do this three things are important:

• Choose the right data.
• Develop data strategy and build intuitive tools and interfaces.
• Adjust culture and mindset. 

Technology

With technology, strategic partnerships are crucial. But there is a challenge here that comes at a cost. Organisations need to change how much they are willing to spend on technology. And that's a challenge because some of us are too smart. You need to capture everything in a way your granny can understand it. You need to simplify it.
Various programmatic operating models include:

Ask agencies to buy programmatically for you.
Plus: Fast, easy to do.
Minus: Brand doesn't own it's data. Nothing flows back to the brand.

Hybrid: Own your data, do some direct buying, but have agencies leverage your data while buying on your behalf.
Plus: Limited investment required, maintain data ownership.
Minus: Agency monitoring required.

Buy all advertising programmatically in-house
Plus: You own your data and eliminate all the middlemen.
Minus: Huge amount of new skills and infrastructure needed in-house to do this well.

Talent

Talent includes the entire organisation. The entire organisation needs to understand the data, because if it's not going to be meaningful, they will not understand how to use it. So we really need to educate people. This is as much about raising the ceiling as it is as much about raising the floor.

There's a number of ways to do this. Going from action guides (that are regularly updated), all the way through to really in-depth training. It's workshop-based training, it's e-learning-based training and you have to make it part of the curriculum so they can see it's part of their development plan.

Technique

More content doesn't always translate into the best results.
Here are some basics avoiding the content trap:

• The right KPI for content is not "number of pieces produced." It's consumer reach, engagement, brand metrics and business impact.
• It's harder to keep quality high with high volumes being produced.
• Content production growth is far outpacing media investment growth.
• Machine learning or content stacks - should not just be built to reach various target audiences or tribes, brilliant basics remain essential.

Conclusion

In conclusion, the goal here is ultimately to ensure that we can translate connected intelligence into compelling advantage across the entire system to ensure growth.

• This includes impression-level data across all media as well as publisher costs
• All commercial data
• Productivity targets

Creating a single source of data fuelled by the right first, second and third-party data (technology).

• Open-sourced to ensure even our strategic partners can leverage the data
• Ultimately resulting in improved analytics – providing robust insights and foresight to create value for our business.