MutualMind (discontinued) vs. zefr

• MutualMind gives us a view into the reach of social content we produce on behalf of our advertisers and the engagement that content generates with shoppers.

• MutualMind gauges sentiment around social conversations but does so with the standard margin of error found in most social analytics products. The nature of human conversation makes it difficult for a machine to categorize sentiment with 100% accuracy. MutualMind gets sentiment right between 50% to 70% which is within acceptable industry averages for this type of product. With additional tuning (which MutualMind provides) the accuracy levels will increase.

Reliability and flexibility (MutualMind's willingness to jointly produce new functionality)

As a company that's only 3 years old, MutualMind's toolset is quite usable but it could use some tweaks in the user interface, which they are constantly working on.

During a recent upgrade period, MutualMind had a small window of unavailability. I am confident they have addressed the root cause and do not foresee any future issues.

The product's performance has improved greatly in the last year and we anticipate seeing additional improvements in coming months based no planned infrastructure changes.

MutualMind has always been quick to address any issues or questions we have.

Not really...MutualMind was very professional and helped with all stages of our setup and implementation.

As mentioned before, Radian6 and Sysomos Heartbeat.

• By showing increases in engagement and share of voice (defined as the amount of content generated for our advertisers versus the amount of content generated for their competitors over time) we are able to correlate content to incremental sales data provided by our advertisers.