Optimize Campaign ROI With Predictive Social Analytics

As Mark Twain once said, “It ain't what you don't know that gets you into trouble. It's what you know for sure that just ain't so.” This is particularly poignant when looking at social programs and campaigns.

Successful brands are taking strategic advantage of using social data and social analytics to build more insightful and customer-driven campaigns that realize business impact and social return on investment.

As Mark Twain once said, “It ain’t what you don’t know that gets you into trouble. It’s what you know for sure that just ain’t so.” This is particularly poignant when looking at social programs and campaigns. Thinking you know what will resonate or drive success without research is the kiss of death.

Launching a social campaign without conducting a thorough social analysis of your target markets, segments, consumers and past campaigns can lead to subpar results. It is critical to use social listening and social analytics to really understand the data and, in turn, fuel campaign creative and strategy, which will boost the performance of your campaigns.

I recently published a piece on the progression path from social listening to social intelligence and the use cases and business drivers that are generally followed through this maturing of your social program, and campaign measurement is one of the foundational use cases that drives sophistication and adoption of your social programs. Feel free to dig deeper into the key business use cases that I see driving this adoption here.

Below is a breakdown of the four quadrants of success/failure into which campaigns can fall, based on budget and results. I have plotted the results here based on a Social Reputation Score.


Social Reputation Scores allow organizations to understand how they compare to their competitors within their markets, and against other markets, by analyzing customer satisfaction in real time. Brands use SRS as a business metric for customer satisfaction, as well as for industry benchmarking, competitive analysis, campaign measurement and crisis monitoring.

However your campaigns are performing now, it’s important to focus your key performance indicators on shifting your campaigns toward the top left-hand “major success” quadrant of the chart.

As you run more campaigns, gather more data and apply more sophisticated social analytics on the performance of your campaigns, you can begin to correlate campaign specifics, which can include content types, timing, duration and target market. Over time, the analysis will illuminate the types of campaigns that are likely to produce the strongest results and highest social ROI for your business.

Underperforming campaigns fall into a variety of categories. The most common, visualized by the charts below, are typically referred to within the social intelligence industry as “flop,” “bad buzz” and “no spread.” A campaign that flops is one that fails to produce any significant or sustained increase in buzz. A bad buzz campaign is one that generates a boost in buzz–but most of it negative. Finally, a no spread campaign is one that produces a very brief and unsustainable, although significant, increase in buzz.


With these examples of underperforming campaigns in mind, let’s take a look at what a high-performing campaign might look like:


While this is just one example of a successful campaign, there are repeatable key points that can be applied to your campaign measurement methodology. Ideally, the start of a new campaign will quickly generate a sustained (and steep) upward slope in positive buzz volume (as seen above), which should peak somewhere in the range of four to 10 times your pre-campaign volume baseline.

How long it takes to reach this peak depends on a number of factors, including the mediums in which your campaign material is appearing, the frequency of content placement, virality and more. Once your campaign has reached its peak, there should then be a gradual downslope of sustained positive buzz. This drop-off will ideally level out to a post-campaign baseline that is markedly, if not greatly, higher than your pre-campaign baseline.

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