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Developments and Challenges in Social Media Measurement

Agenda

Who is this guy?

Déjà vu all over again

A game of Chutes and Ladders

Light at the end of the tunnel?

Who is this guy?

• 20 years research/analytics experience

• Focus on media: Turner Networks, MySpace, Yahoo, media/ad agencies

• Quantitatively focused:

• MMMs• Segmentation Analysis• Campaign Attribution• Behavioral Targeting• Fan/Follower Valuation

Who is this guy?

• The Public Relations discipline took hold of social marketing

• Porter Novelli’s client base is global, which leads to some interesting social media analytics opportunities

Déjà vu all over again

• Dirty data in the social space

• Inappropriate methodologies

• Vendors that do not care about data quality

• No industry standards

Déjà vu all over again

• Data is spam laden

• All tweets are not created equal

• Interactions across social channels mean something different

• Does an emoji connote sentiment? Does it generate influence? How much influence does it generate?

• What is influence worth? What is reputation worth?

Déjà vu all over again

• Because of the sheer volume of data, trying to make sense of this has led some firms down very strange roads

• A common approach is to sample the social conversation, and infer quantitative conclusions

• This is in defiance of the Central Limit Theorem

Déjà vu all over again

• On my arrival into the public relations industry, I took as many vendor meetings as I could. My findings:

• All data vendors have the “best” sentiment scoring engine … though the criteria for this claim is unknown

• Vendor-side spam filtering is ineffective

• The interest across vendors is creating prettier charts with vibrant colors, rather than data quality

“magic beans”

Déjà vu all over again

• There are several groups trying to develop some industry standards around social media measurement, but as of now, there are no accepted standards

• The best we have at the moment are the Barcelona Principles

• Will social media ever get to the same level of standards as the IAB/WAA on online media measurement?

Chutes and Ladders

• “Every thing is measurable”

• The reason that standards were developed on the web analytics side was due to the investment

• Public relations wants more marketing dollars

• Standards are coming out, but are they strong enough?

Where: E = excused from flyingI = insanityR = requests an evaluation

Chutes and Ladders

• Is the objective of the social analytics qualitative insights mining, measurement, or both?

• If sampling leads to inappropriate or insufficient conclusions what are the measurement options?

• In the web analytics world, we take spam filtration for granted; in social, relevance is everything.

• Every social analytics program is going to have error … some known and some unknown.

Light at the end of the tunnel?

• There are platforms that allow a full analysis of text … some are robust and offer easy ways to integrate text and other data into one reporting platform

• The solution that we have developed is using an open source text analytics platform, so we effectively built our own solution

Light at the end of the tunnel?

• People talk about brands, products and services using a specific ontology

• “Sick” connotes “good” for some categories, “bad” for others

• Most vendors who provide sentiment scoring across the entire universe of conversation are not able to account for these differences

Light at the end of the tunnel?

Process:

• Pull in data from multiple sources

• Build dictionary and grammar rules

• Categorize text by conversation category and sentiment based on rules (human and machine learning algorithms)

• Human scoring and validation

• Dump results to UI

Best Practices

• Any vendor who talks about “best” sentiment engine – based on what?

• Know your data

• Get as close to the source as you can

• Solutions custom to your needs are always better than out-of-the-box

• Beware of pretty Uis

• Good governance of data and analytics

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Questions?