Creativity + Data = Ruder Finn Beacon

While Creativity is still king, the ability to assimilate real-time data from multiple sources, and convert them to valuable insights that lead to action, is a critical success factor for CEOs and CMOs today. Clients have been telling us that while the advertising side of the house has been comfortable with data for decades, comms and social teams have been struggling to wring meaningful intelligence from the copious amounts of data they collect.

That’s why we created Ruder Finn Beacon, our proprietary Insights & Analytics suite that helps clients derive practical intelligence from big data directly applicable to business goals.

We’re not just talking about marketing-related data such as social listening, influencer maps, consumer journeys, web analytics and media coverage, but any kind of data. If it has a time-stamp and can be plotted on a scale, Beacon can analyse it.

Beacon already includes:

  • Intelligent Listening with Augmentations
  • Influencer Mapping
  • Social Visualisation

With more to come as we refine the I&A suite continuously.

Intelligent Listening

Beacon Intelligent Listening (BIL) is the social listening that we are familiar with, with a few key differentiators. First, Beacon can support and integrate multiple social listening services, for example letting regional teams aggregate social listening across markets. If the client does not currently use a social listening service, we offer Crimson Hexagon as an option.

Beacon monitors online and social media globally including news sites, Facebook, Twitter and Instagram.

We’ve also seamlessly integrated Google Cloud Artificial Intelligence (AI) to analyse sentiment and translate posts on the fly, making crisis monitoring and predictive analytics even more responsive and accurate. At launch we already support automatic translation of over 100 languages, enabling us to cover practically the entire world. It doesn’t matter if you’re tracking Malay, Thai, Korean, Chinese or Tagalog…the posts are there in the Beacon dashboard, translated automatically, analysed in real-time.

Beacon also introduces the concept of Augmentations, which lets us layer any kind of data over listening data, and find correlations. With Augmentations, we can import data of any kind, and analyse that alongside standard marketing data such as web traffic, advertising spend data, e-commerce sales, and so on. Augmentation data sets can range from retail foot traffic to weather patterns.

Influencer Mapping

We’ve partnered with celebrity KOLs and large-scale influencers for many years, but now there’s a way to find micro-KOLs too.

Beacon Influencer Mapping (BIM) discovers and scores social media influencers to help brands quickly design outreach campaigns and build communities. We evaluate and score influencers by Reach, Resonance, Relevance, and Receptivity, creating a map of potential influence.

Micro-influencer mapping is a particularly powerful application of Influencer Mapping, allowing brands to discover influencers with followers numbering only in the thousands or tens of thousands, yet that are passionate and influential around a niche topic. For example, Beacon was successfully used by a major pharmaceutical company to map and rank the most passionate online influencers surrounding a specific disease, leading to more targeted engagement.

Social Visualisation

Many client brands manage multiple social media accounts, each with unique audiences that overlap and cross-influence. Ironically, Facebook’s Insights tool contains a large amount of user data that can overwhelm marketers and make deriving insights a challenge. BEACON’s Social Visualisation dashboard collects a large amount of this performance data, then presents them in easy-to-understand insight charts that make interpretation straightforward. Supplemented by expert recommendations from Ruder Finn’s social media experts, BEACON Social Visualisation delivers actionable insights that allow brands to outperform their peers across a multitude of KPIs, from engagement to conversion.

Beacon is already serving multinational brands across Asia today.  For a demo or pricing information, please drop us a note at Beacon@RFI.Asia.


Targeting 101 (or, calling them Millennials is so 2014)

Labels are just labels. People are messy and contradictory.

Our need for patterns helps us make sense of the world, it’s how our brains are wired, but it doesn’t always make it easy to predict behavior. In fact, seeing patterns and labelling a group as a stereotype can be counterproductive these days.

We were tasked by a client to “target millennials” for a campaign, so we conducted research and created a series of personas of this group, including “affluent millennials”, “lifestyle millennials” and so on, within a certain geography. Labelling a specific age segment with an aspect of their generation’s consumption habits can be risky, but it was useful for the campaign because we were mapping specific product attributes to specific behavior. What we couldn’t get the client to understand though, was that they could target product attributes to behavior while ignoring common demographics like age, income and gender.  For example, there are people in their 20s who will pay over a hundred dollars for a nice cab sav, in the same way that there are forty-year-olds who skydive on vacation. You may call them the long tail, but bucking trends is the trend these days.

So what is the new approach to targeting?

Target by behavior, not gender or age. Microtargeting on social platforms makes it relatively straightforward to deliver content to targeted audiences, but many marketers make the mistake of targeting by broad stroke demographics, not behavior. Not all Justin Bieber fans are aged between 14-25; many scuba divers are above 55. Age is no longer a reliable predictor of behavior. Targeting affluent travelers? Aim your social content at people who have traveled overseas at least once the past month, and who have liked the brand pages of relevant airlines and high-end hotel groups.

Mine data to spot non-obvious patterns that predict future behavior. For example, Target, a large American department store, identified 25 products that women expecting commonly purchased together, and sent coupons to them. In the process, they inadvertently outed one girl’s hidden pregnancy to her dad. Here’s what happened:

[A] man walked into a Target outside Minneapolis and demanded to see the manager. He was clutching coupons that had been sent to his daughter, and he was angry, according to an employee who participated in the conversation.

“My daughter got this in the mail!” he said. “She’s still in high school, and you’re sending her coupons for baby clothes and cribs? Are you trying to encourage her to get pregnant?”

The manager didn’t have any idea what the man was talking about. He looked at the mailer. Sure enough, it was addressed to the man’s daughter and contained advertisements for maternity clothing, nursery furniture and pictures of smiling infants. The manager apologized and then called a few days later to apologize again.

On the phone, though, the father was somewhat abashed. “I had a talk with my daughter,” he said. “It turns out there’s been some activities in my house I haven’t been completely aware of. She’s due in August. I owe you an apology.”

You can read the original New York Times story here.

In a nutshell, as marketers we should start with behavior, instead of making assumptions based on demographics. Straightforward and obvious, right?