Earned, paid, and owned media are distinct species. If you haven’t laid out cash for a mention of your brand, product, or personnel in a media outlet, whether online or social, you’re deemed to have earned the coverage. (Take “earned” with a grain of salt. You may have laid out big bucks for a publicist or efforts to build your brand’s visibility.) If you’ve bought the coverage — advertising, for instance — that’s paid. And if it’s your outlet, then that media is owned.
Whether media is earned, paid, or owned, you want to measure the extent of attention and the effectiveness of your message. The effort can get quite involved, when multiple channels and multiple exposures are in the mix. The get a precise picture, you have to engage in attribution modeling. When social platforms come into play, the effort can be substantial.
General social business challenges, and technical responses, are central topics at LT-Accelerate, a unique European conference, taking place December 4-5, 2014 in Brussels. We’ll have Roland Fiege of IPG Mediabrands speaking, on methodologies and tools for measuring the earned value of brand social-media activity. If this topic interests you as well, you’ll want to learn more. A quick Q&A I recently conducted with Roland is a start, then I hope you’ll join us in Brussels. First a brief bio –
Roland Fiege is head of social strategy at Mediabrands Social, home of Performly. In his spare time, he is working on a PhD project researching methodologies for measuring the value add of marketing on Facebook and Twitter. And next, -
Our interview with Roland Fiege
Q1: The topic of this Q&A is social media analytics. What’s your personal SMA background and your current work role?
Roland Fiege: My personal SMA background started with consulting projects evaluating social media listening systems back in 2009. In 2010-11, I was part of an international team at US technology company MicroStrategy that developed a solution that analyzed the social graphs of Facebook users to help brands to understand the interests and affinities of their “fans” better.
In my current work role, we analyze user interactions responding to brand messages on social media channels and have developed a model that attributes an monetary “earned media value” to these interactions. This allows brands to quantify and valuate the outcome of their social media investments.
In my current work role, we analyze user interactions responding to brand messages on social media channels and have developed a model that attributes an monetary “earned media value” to these interactions. This allows brands to quantify and valuate the outcome of their social media investments.
Q2: What are key technical and business goals of the analyses you’re involved in?
Roland Fiege: The technical challenges are to keep the solution up to date with ongoing API changes by the most popular social networks and how to loop back “real time” bidding price benchmarks into our systems (vs. a static benchmark). Another challenge is to meet the EU data privacy standards that enterprises,German especially, try to comply with.
Business-wise, the challenge is to establish a common understanding how to attribute and valuate user interactions.
Business-wise, the challenge is to establish a common understanding how to attribute and valuate user interactions.
Q3: And what particular analytics approaches or technologies do you favor, whether for text, network, geospatial, behavioral, or other analyses?
Roland Fiege: We basically gave up on automated text analysis when it comes to sentiment. It never worked in Europe with all the different languages, dialects, irony etc. There was too much manual work involved that clients were not willing to pay for.
Currently we concentrate on the quantification for user engagement and its financial valuation.
Q4: To what extent do you get into sentiment and subjective information?
Roland Fiege: Our experience is that if users like, share, and comment on brand content, it mostly is positive or neutral sentiment involved. Contrary to this, most user posts on brand channels are negative and in correlation with negative customer experiences. Since we measure the monetary value of brand communication, we only measure fans/follower interactions on brand content.
Q5: How do you recommend dealing with high-volume, high-velocity, diverse social postings — to ensure that analyses draw on the most complete and relevant data available and deliver the most accurate results possible?
Roland Fiege: We do not only rely on the APIs that Twitter, Facebook and YouTube (Google) provide but also user other (fire hose) data providers to get the most complete picture/dataset, also for retrospective analysis.
Q6: Could you provide an example (or two) that illustrates really well what you’ve been able to accomplish via SMA, that demonstrate strong ROI?
Roland Fiege: What we accomplish: Clients manage to optimize their content strategies in near real time, can compare the performance of their content (agencies) in different regions and countries, and can identify savings potential in the millions. It is the first time brands can calculate the total cost of ownership of their social media channels and have a clear Input vs. Outcome result all condensed into one KPI: Money.
Q7: I’m glad you’ll be speaking at LT-Accelerate. Please tell me about your presentation, briefly: What attendees will learn.
Roland Fiege: In this talk you will learn about the latest methodologies and tools to measure the Earned Media value of a brand’s activities on Facebook, Twitter and YouTube in hard currency.
Q8: Finally, do you have recommendations to share, regarding choice of data sources, metrics, analytical methods, and visualizations, in order to best align with desired business outcome?
I will share those in my presentation in as much detail as possible.
Thank you, Roland, for your responses. I’m looking forward to hearing more, at LT-Accelerate in Brussels.
This Interview has been done by Mr. Seth Grimes, the leading industry analyst covering text analytics, sentiment analysis, and analysis on the confluence of structured and unstructured data sources and founder of Alta Plana Corp.
No comments:
Post a Comment