Warren Sukernek shared this presentation recently and it hit home on a variety of fronts. As we spend time with clients working through social media monitoring, we find more and more examples of how it’s not a precise science. Sitting side by side with folks who work every day in detailed web analytics who continually look for ways to optimize PPC spend, our social media team has experienced first hand many challenges outlined in Marshall Sponder’s presentation. Some points that resonated strongly:
Sentiment analysis today is too much like Quantum Physics
There is a lot of manual work to determine influencer lists
Social media monitoring tools are not capable of advanced meme clustering or semantic analysis
Clients ask all the time around geo-location – the science to identify local influencers and posts is crucial to many businesses and these tools aren’t anywhere near perfect
As for predicting the future? Integration to CRM and web analytics, factoring in new technologies like Google Sidewiki, and evolution to standard business intelligence practices. Keyword tools will help down the road too – curious if the same that help with PPC and SEO optimization will apply here. This is a practical, thoughtful guide on where social media monitoring has room to mature. For now, my experience is showing that labor (smart, social media savvy, analytical folks) is making up the difference, but it’s challenging to “read the tea leaves.” What is your experience?
Few marketers dispute PPC as an effective and measurable online channel. Social media, in contrast, is currently subject to dispute.
One of the more compelling arguments for pay-per-click search marketing is the ability to attribute web sales directly to clicks from search advertising. ROI can be measured to multiple decimal points tying the amount of spend invested in bidding on keywords to the direct revenue and conversion. When the conversation changes to social media, there are debates about ROI, a lack of proven approaches and many marketers still viewing social media as experimental. [“Conversion” for those not familiar with web analytics is defined as a visitor to a web property who completes a targeted action, including signing up for an email newsletter, adding a product to a shopping cart, or completing checkout.]
Skepticism Abounds
A way to address the skepticism marketers have about social media is to draw the same correlation to the purchase path as search marketing. Notice I did not suggest “the” way to address the skepticism — providing better metrics won’t give the complete picture of social media benefits, but it will start to quantify the role social media can play in a marketing strategy in terms that internet marketers deal with already. For example, today Webtrends and Radian6 made a joint product announcement tying traditional web analytics to social media monitoring, through Webtrends’ Open Exchange platform. This is just the tip of the iceberg.
Establishing Credit
Traditional analytics tools give credit for conversion to the tracked marketing activity before the conversion takes place – a “last click” methodology. This could be a search query prior to a site visit, an ad clicked through on a search results page or a banner ad. Those in the SEM and Display Advertising industries would tell you that while these metrics are precisely measured, a major challenge is to quantify all the “other” touchpoints a consumer has prior to conversion. (Rosetta, my agency, has a differentiated approach to marketing analytics that does capture “view-thru” – tracking that a user saw a display ad days or even weeks prior to a conversion event).
Here is what I would like to see analytics vendors or social media monitoring platforms do to start to quantify the measurement:
Track participation in social technologies in similar fashion to traditional ecommerce sites (defined conversion events, page views, length of visit). A potential limitation is that brands may only be able to track measurements based on assets they control (hosted communities, hosted blogs, custom widgets, etc).
Tie search engine queries, organic search site visits and PPC ad clicks – and ultimately, conversion – back to whether the user had participated in a social technology, and measure typical length of visit/level of engagement both before and after conversion.
Provide in one dashboard the ability to identify the direct correlation between social marketing initiatives to conversion and revenue.
This level of data would help marketers more directly measure the success of social marketing initiaitves and make at least part of the intangible, tangible. Is that a lot to ask?