Faster business decision-making based on organic customer data  

Editor’s note: Bernard Brenner is senior director, modern work, security/compliance/identity and social intelligence research, Microsoft. He is based in Redmond, Wash. 

Developing fresh, innovative ways to harness customer insight is a top priority for the Research + Insights (R + I) team at Microsoft. We are on a continuous quest to pioneer new ways of gathering timely, affordable, unbiased customer insights, which allow for quicker business decision-making. The social satisfaction methodology is an approach to understanding the voice-of-the-customer that can be applied across any products or services. This methodology leverages social media data, collected across various platforms (Twitter, Reddit, blogs/forums, customer reviews, etc.), that is then mined to understand the themes driving positive and negative experiences with Microsoft products and services in real-time. 

There are several advantages to using the social satisfaction methodology over traditional research methods, primarily time and cost. Using traditional marketing research techniques, a product satisfaction study would take about two months to complete and cost nearly $250,000. Using a social satisfaction study offers not only a comprehensive and descriptive look at the same topic, but it also cuts down on the opportunity cost of waiting for insights to influence strategy and execution. We can provide answers in a couple of weeks for about $15K-$20K.

Additionally, the social satisfaction method utilizes the organic, unprompted, voice of the customer to offer more tangible and descriptive insights on likes and dislikes of the product experience. In traditional research, the design of the questionnaire can limit product feedback, creating survey bias that accompanies every study we deploy. The beauty of social data is that a structured question is never even posed. It uses query logic to find and analyze organic customer conversations.

Faster business decision-making  

When the pandemic hit, businesses were suddenly thrust into the complexities of working from home. One of those complexities included ensuring that workers had the tools to collaborate and communicate. As such, millions of information workers, from small and large companies, had to quickly adopt and learn how to use new collaboration products (such as Teams, Zoom, Meet, GoToMeeting) to continue with their work. 

With so many information workers new to using these products, the Microsoft Teams Product Marketing team sought to understand how these unaccustomed users were experiencing Teams, specifically relative to competitive users. Normally, our team would have conducted a product satisfaction study that might take two or more months to complete. However, with the growth in collaboration tool usage happening so quickly, we knew that we would not be able to help influence any decisions with that kind methodological latency. At the time, we also didn’t know for how long the growth was going to happen and if it was going to be sustained. So, choosing the social satisfaction methodology was truly the only option. 

The study we conducted looked across the various social platforms and identified people who were talking about their experiences with Teams. Looking specifically at the themes behind positive and negative experience, we were able to quicky identify the key areas that were both enhancing and detracting from our customer experience. Though it did not provide a product satisfaction metric, it did provide comprehensive detail on how customers experienced Teams as well as competitive products. We were able to use that data to inform marketing messaging as well as to communicate to engineering what was driving these experiences (good or bad). We could also tell them what customers liked about our competitors, providing insight into what was driving positive and negative experiences. This valuable information led to quick-turn decisions for improved product messaging strategies and pathed the way toward product improvements for Teams. And all of it within the rapidly growing and crowded communication tool landscape at the onset of the pandemic. 

Teams social analysis key findings: 

  • Initial trials of Teams were generally positive, but a desire to see more peoples’ faces within video calls was cited as a reason for choosing Zoom over Teams. 
  • Security was a big issue for Zoom. The data showed security is mentioned equally between the two, but when it’s mentioned for Teams, it’s in a much more positive context. 
  • Zoom had an exceedingly high association to Meetings, indicating that Zoom was seen primarily as a point solution. Teams was seen as having more scale across the collaboration experience. 
  • Positive experiences with Teams were concentrated in mentions regarding workplace usage and remote learning; users shared features they liked and praised Teams for its ease of use. 
  • The themes around Teams were significantly more diverse than Zoom (inclusive of file storage, chat, channels) indicating that users saw the robustness and diversity of its product offering. 

Organic voice of the customer 

The social satisfaction method can also be tooled in a way to harvest information to gauge the success of a product launch. Through advanced query creation and management, we can identify initial adopters and see what people are saying about their early experience with the products. Social satisfaction is a perfect methodology for a product launch because the audiences (security practitioners, IT Pros, information workers, etc.) are highly involved in social and tend to post about very technical aspects of their experience that can be overlooked when writing a questionnaire. 

We implemented this social methodology during the Windows 11 Global Availability release in November 2021. To give Microsoft leadership and product teams a high-level snapshot of general sentiment, trending opinions and fluctuations of volume during the week following its launch – the social intelligence team sent out 24-hour reports over a seven-day post-launch period. The daily tracking of customer verbatims added color and clarity throughout the analyses process to determine initial product sentiment. Marketers and engineers used the data to both manage launch communications with customers and partners and to help prioritize software enhancements to optimize for the upgrade experience.

Social media is a consumer research gold mine

The biggest advantage of social is that we can do things quickly. As the above examples demonstrate, we can conduct studies now in a matter of days to be at the point of decision. The methodology provides us with 70-80% of the data needed so Microsoft can facilitate faster decisions – which is commensurate with the speed of the technology sector. 

It’s also significantly more budget friendly. The money we spend here is on developing the right queries, testing, iterating on those queries and then harvesting that information. Harvesting requires running it through machine learning and natural language programming to determine the core themes. All of this is about 5-10% of the cost of a primary research study. 

Lastly, we’re able to harness the organic voice of the customer. People who post tend to be highly involved customers and exactly who we want to hear from. They know about our products and our competitive products. So, they have more actionable and insightful information than just a general consumer or respondent. And the cherry on top? We can replicate this methodology across all lines of business – from the new Windows launch, to when new Surface products are released, to when we make enhancements to Microsoft 365, or release a new video game series. To turn a phrase, social satisfaction gives us more bang for the buck.