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SparkScore (The Social Net Promoter Score): A methodology for measuring social customer loyalty — Live from the Measurement Pre-Conference

Coverage of this session by Kristen Platt of Connect with her by following her on Twitter.

10:15 —’s Megan Uithoven introduces Satmetrix’s VP of Innovation & Strategy, Laura Brooks.

10:16 — Laura: Who has heard of the Net Promoter Score? (Lots of hands.) “Good, this is a transition of that score.”

10:17 — SparkScore is a standardized metric which conveys the insight from structured, survey-based solutions to the “social universe.” The key thing: It’s not just about the metric — it’s about what you do with it.

The purpose of SparkScore is to simplify the big social analytics business challenges into one key metric that will represent customer loyalty. Social is a key channel.

10:18 — Laura: There’s a tremendous volume out there, what do you pay attention to? How do you decide what to act on and prioritize? Sometimes it’s difficult to identify a root cause: What are your customers talking about and why?

10:19 — Laura shares an example of a brand detractor and breaks down the SparkScore. They score the social post as a whole, including sentiment value, loyalty analytics, and key drivers that affect loyalty.

10:20 — The score parses out each individual sentence and idea in the detractors/advocates’ social post. They only analyze the ideas that provide value to your metrics.

10:22 — NPS and SparkScore are all tied to change and making a difference in the organization.

10:23 — It was developed using structured survey data and comments. We gathered social data to compare and contrast the learning, algorithms, and metrics from NPS and SparkScore. We then verified this using research data pilots.

There are currently 7 domains of companies using SparkScore.

10:25 — Laura: How it works: We pull major social channels reviews from customers. Then we filter for brand and other competition. We create a SparkScore for the sentiment and apply it to your dashboards.

10:27 — Laura says SparkScore goes beyond social listening.


  • Create a data collection engine to accurately measure SparkScore.
  • Identify root cause analytics
  • Benchmark against competitors: Share of voice is not everything.

10:29 — “Trends of data are sensitive to shifts in operations.” Laura shares an example from a banking client.

10:30 — Laura: SparkScore is not only for B2C companies. It also gives product insight by stack ranking against key competitors for B2B business.

10:32 — Laura: The plural of anecdote does not equal data.

10:34 — The score is easily dissectible: You can track the customer’s root cause of his or her particular review.

10:35 — Laura: With SparkScore, you can take action and “close the loop.” Keywords and change scores help you detect the right action that needs to be taken within your company to help the customer.

Bottom line: It supports the full life cycle of social measurement and engagement.

Q & A:

Q: Does a social share equal a recommendation? How to account for Net Promoter score for social channels that don’t allow that data pulling?

A: The crawling can actually detect where people are talking (which channels). It doesn’t reach Yelp yet, but we are still trying to work with these platforms to create a partnership in order to get that data.

Q: What do we do about the customers that continue to keep liking our social pages, posts, etc.? How do we determine unique likes?

A: If someone is out there saying positive things about you, other people are listening. I personally view your situation as multiple positives. If you wanted to exclude that person in your SparkScore, we could count them as only one person.

Q: When you look at social data, people are talking all the time (as opposed to a question of recommending a certain company (y/n).) How do you differentiate?

A: We’re not tracking individuals here. We focus more on groups and trends of a particular brand sentiment.

Q: How can a local brand compare a share of voice with national competitors?

A: You can put national competitors in your competitor profile. Regional data is tough: it becomes more of a proportion of local vs. national data and voice.

December 9, 2013 0 comments

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