Producing expert-written content for highly technical markets is our strength. However, something our customers have come to depend on as part of that service is help with developing topics for their blogs and longer-form content marketing assets. We certainly encourage you to develop your own topic strategy. However, part of our partnership with our customers involves helping them generate a topic for each piece of practitioner-written content we deliver to them.
We write this series to help our customers and marketing managers look under the hood to discover how we develop topics using SoV and SoC as metrics. We always begin with SoV calculations for specific conversations, and then use that data to inform our topic selection.
Today, we take a look at API monitoring. API monitoring is the practice of monitoring application programming interfaces in production to gain visibility into API performance, availability and functional correctness.
May 2018 API Monitoring — Conversation Topic Interest Over Time by Google Trends
A Metrics-First Approach
Our approach to determining topics within this conversation begins and ends with a share of voice (SoV) calculation, which ultimately gives us an idea of a vendor’s share of this conversation (SoC). Our share of voice methodology is described in some detail in a variety of places, but here is a quick summary:
Share of conversation is the percentage of any specific conversation you own. SoC is more precise because it looks at specific conversations within a market versus focusing only on global SoV compared to competitors. While it’s interesting to know how your brand or product is doing in the world of all products, you can make the greatest impact by going local with specific conversations.
API Monitoring for May 2018
Below, we will dig deeper into why the results were the way they were.
Fixate’s Re:each platform has algorithms which derive conversation share of voice across traditional and social media. The phases of calculation are data collection, normalization, and interpretation. We can’t give you the secret sauce, but we can give you an idea of how we do it.
Re:each Conversation SoV Results from May 2018 for API Monitoring
- Identify your place: Identify specific keywords and concepts associated with your brand and product based on those concepts that appear the most in all conversations you participate in.
- Determine your conversations: From there, the concepts are applied across a body of sources in order to identify the three conversations which are most relevant to you. For each vendor, there are three types of conversations identified:
- Demand Gen
- Mindshare/Thought Leadership
- Find your competition: Competition is derived by identifying the top 4-9 vendors in each conversation based on their SoV in those conversations.
- Determining relevant topics: Topic suggestions are derived from entity/concept extraction of content that was most prevalent in each conversation selected over the set period of time. Those concepts that had the greatest reach in that conversation are weighted and end up as the core elements of a suggestion.
Data is collected from traditional social media sources as well as trusted media sources for each broad market. Weight is put on content based on the source it came from using a proprietary algorithm. Currently, calculations are done at the end of each month for the entire month’s worth of data.
The machine learning used in SoV is human-supervised (Human-in-the-Loop). SoV calculations can be fully automated; however, topic suggestions are subject to language challenges, and domain expertise based on raw data collection. Domain experts validate SoV calculations, and reformulate raw entity extraction on top-performing content in each conversation to build coherent topic suggestions.
May 2018 Sources that Influenced Topic Selection and SoC for API Monitoring
In May, there were no big stories of note driving the conversation. Instead, the biggest SoC drivers came from technical blogs about best practices and implementation.
Technical Blog Posts
Content matters—especially in the API monitoring conversation. SmartBear syndicated content from their blog onto DZone.com and received the four highest-ranking blogs:
- 5 Reasons Why Product Managers Need to Care About API Performance Management
- Best Practices For Reducing Downtime on the Way to Production
- QA in a Microservices World
- 4 Reasons Why You Should Monitor Your API Transactions with New Multi-Step Monitors in AlertSite
Members of FIxate.io’s team offered top blog content: Chris Tozzi’s article about infrastructure and application monitoring stood out on IT Pro, and Cordny Nederkoorn’s blog titled “QA and API Monitoring” made a splash via Fixate.io’s media site, Sweetcode.io.
- Eric Vanderburg Twitter account -Tweet on May 3rd highlighting SmartBear AlertSite capabilities.
- Rando Hütt Twitter — frequent Tweets about API monitoring
- Dr. Craig Brown Facebook Page —self-proclaimed “Techpreneur,” with 33k followers
The practitioners ideal for producing content on API monitoring are backend developers in organizations who have API-First development practices. For many, API development is an afterthought. But for those companies who build their APIs even before their core functionality, they have great respect for the need for API monitoring, and a lot of experience in building it. They will be professional, making sure that APIs are developed correctly, tested correctly, and maintained. And they will also have the experience that ties into the fallout when API services go down.