Home Data-Driven Thinking Data: Define The Rules, Seize The Opportunity

Data: Define The Rules, Seize The Opportunity

SHARE:

thaernamruti“Data-Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media.

Today’s column is written by Thaer Namruti, European strategy director at Acxiom.

Before you can score points in any game, you need to know the rules. How is “winning” or “success” defined?

In data-driven marketing, some might equate scoring points with using data to more effectively engage consumers. But defining the field of play and rules of the game first should be fundamental.

While most advertisers set broad KPIs for success aligned to strategic marketing goals, the measurement of that success is only as good as the data behind it. Understanding exactly what data is needed to track success is as important as recognizing the need to track in the first place.

How Do You Measure Success

“Success” can vary, depending on the company. Every brand has its own personality, so it’s important to ensure targets reflect their ultimate objective. Performance-driven brands, such as Bet365 and Hertz, may focus on lead generation, for example, while the Coca-Colas and Apples of the world may want nothing more than for consumers to love their brands beyond all reason.

Market-growing brands may want to take a more personalized approach to promote greater awareness, increase the number of touchpoints with customers and build a larger share of voice. For example, it might want to target 1 million males aged 18 to 34 years old to promote a new range of facial treatments for men. Using mass-reach targeting, such as addressable TV campaigns, powered by a blend of premium publisher and first-party data, brands can connect live conversations on social channels and then correlate these to real-time retail sales data.

This highlights which customers are engaged with their brand and those who actually purchased their product. This ultimately delivers a far greater level of insight and allows brands to see how effective their marketing strategy has been.

On the other hand, bigger and more established brands don’t need mass awareness. Everyone already knows Coca-Cola. Instead they want to form deeper connections with customers. This could mean using social platforms to reach a highly targeted set of individuals. This personal and direct approach is an extremely effective way of generating fervent, ambassadorial brand love among your fan base.

For example, last year’s “Share a Coke” campaign encouraged people to post photos of their names on bottles and cans across the globe. The end goal of this campaign was to increase Coca-Cola’s share of voice across social channels and engagement with customers, so the next time they go into a corner store they will theoretically choose Coke over Pepsi because they feel an affinity to the brand. I myself can testify that my kids go straight past Pepsi to search for their names on Coke bottles.

Both objectives and strategies look different in practice and in measurement, so brands need to decide what success looks like to them from the start. However, this also involves vast amounts of data – a valuable asset if effectively harnessed.

The Importance Of Data

By gradually shifting from traditional approaches focused purely on reach, engagement and action, brands can create a constant flow of information, based on real-time sales or browsing data, connecting their own data. Every marketer should want to know what effect their activity has on their business and, most importantly, their customers.

Brands need to make sure they are in a position to adapt to this wealth of data. While this not only helps to justify budget spending and how it is spread across different channels, by its very definition, it delivers true value and higher ROI. Data strategies need to address the proactive use of data, where the customer journey is anticipated, which is the essence of personalization, and the reactive use of data, or the response to real-time customer signals.

Generating or quantifying this kind of ROI across a brand’s marketing activity has previously been impossible. It has been the cause of many headaches in ad agencies. But teams are beginning to make headway by employing the science of mix modeling, click path analytics, reporting and optimization tools and matching on- and offline data.

Whether it’s generating awareness, driving engagement, improving customer experience or increasing sales, data provides the opportunity brands need to prove their effectiveness and ensure their customers are happy ones.

Follow Acxiom (@Acxiom) and AdExchanger (@adexchanger) on Twitter.

Tagged in:

Must Read

AppLovin Is Back To Smashing Earnings But Investors Are Slow To Buy

AppLovin is growing at a blistering pace, but Wall Street investors remain cautious about the business.

Gamers Love Ad Blockers. So This Site Found Another Way To Show Them Ads

High-end ad blockers mimic some of the same behavior as bot traffic. So WiseGuyGaming repurposed the tools it was already using to identify bots to reveal its ad-blocking audience as well.

Criteo Is A Survivor, But Expanding Beyond Retail Media Will Be Its Toughest Challenge Yet

Criteo has weathered considerable storms in its day, including a painful moment in March 2020 when its market cap bottomed out below $500 million. Can it pull off yet another turnaround?  

Privacy! Commerce! Connected TV! Read all about it. Subscribe to AdExchanger Newsletters

Sports Leagues Can’t Stop Putting Ad Revenue Ahead Of Fan And Player Interests

Disaffection and outright anger toward US sports institutions run deeper than logo-cluttered fields. Leagues and teams are sacrificing player safety and fan enjoyment for marketing dollars.

Comic: Traffic Jam

With Search Traffic Down 70%, People Inc. Bets On Revenue Beyond Site Visits

People Inc.’s referral traffic from Google search is down 70% over the past two years, and by 26% in Q3 alone. But its digital revenue is still growing, albeit slowly.

Chord Buys Its Rival Zenlytic To Build An Agentic Version Of A CDP

On Tuesday, Chord, a six-year-old commerce tech startup, acquired Zenlytic, an AI startup with an anthropomorphized data analyst agent named “Zoë,” for $5 million.