Using social listening data to watch software and respond to outages
Henry Chapman, Research and Insights Analyst
Software outages and brand havoc
Customers dislike it when their software stops working. These outages alienate your clients and damage your brand. While it’s true for relatively minor outages, like when customers can't order a burger on the McDonald's app, it becomes even more infuriating when it's where their finances are held, like banking, brokerage, or investing software.
Customers of Fidelity Investments, the second largest brokerage in the United States, experienced such an outage on August 15, 2023. For a few hours, customers could log in but could not buy or sell stocks or even see any account balances. Clients took to social media to express their fear as to when they could access their money again.
We used a customized social listening dataset using Infegy Atlas to identify the outage and quantify its brand consequences. We'll identify the key indicators we used to show evidence of the issue and its damage to your brand so your brand can do the same with your social listening tool.
Traditional ways of detecting outages
When software gets buggy, developers can use two types of data sources to determine what's wrong. First, developers put error-handling signals such as logging in their code to catch errors. Logs help developers know if their app is working as it should and help them troubleshoot problems after identification. Since all this data is private and internal data doesn't harm a brand's reputation.
Second, there's public data from websites like www.downdetector.com. These sites rely on crowdsourced outage data that users self-report when they can't access a web resource.
Social listening data can also be a public outage indicator showing your application isn't working. Next, we'll discuss what social listening indicators you can use to identify software outages and how to respond.
Surge in post volume
Post volume is the first social listening indicator that something might be up with your product or service. Traditionally, r/FidelityInvestments is a sleepy place. It usually garners between 200 and 300 comments per day in August. This lack of activity makes sense: August is a summer month and traditionally quiet for the investing community. However, on the outage day, the subreddit rose 187% from its two-week mean of 348 posts. Here is your first indicator that something was afoot within the Fidelity community.
Rising negative sentiment
While post volume is a great first indicator to detect anomalous behavior about your software product, it's not sufficient to suggest that something terrible is happening.
To detect the brand concern, we next turned to aggregated sentiment. Traditionally, r/FidelityInvestments is a neutral place, meaning that positive sentiment roughly equals negative sentiment. However, on the outage day, we saw a two-week high surge in negative sentiment. Negative sentiment reached 72%, approximately three out of every four posts.
Identifying negative keywords
We've detected anomalous post volume and negative sentiment around your brand at this stage. It's time to dig deeper into what the actual problem is.
To do this, we'll use Infegy Atlas's Topics, which aggregates nouns and verbs that are particularly important within chunks of text. On August 15, we see apparent keywords like "access," "service," "outages," "logging," "problem," and "website" that rise to the top of aggregation. These all have primarily negative sentiments, another clue that something's wrong. If you set automated alerts, you can use these aggregated indicators to show that something is wrong with your application and that the issue is widespread, suggesting many users are experiencing the same problem.
Indicator emotions drop
Now that we've looked at aggregated sentiment and topics let's look at how those meld together to create waves and both positive and negative emotions about your brand. Infegy Atlas achieves this with Infegy IQ, our natural language processing engine.In analyzing emotions on r/FidelityInvestments, we find that Joy and Trust are the most predominant. High Joy and Trust makes sense: Fidelity is a legacy investment community player with a sterling reputation for excellent customer service and software uptime. However, we observed both Joy and Trust dropping precipitously on the outage day. On the negative side, we saw both Anger and Hate rise to take their place. These anomalies are behavior that we don't typically see - for the past two weeks, there has been no point where Anger surpassed Trust and Joy. Developers or brand strategists could set indicators for emotions to clue them into a problem so they can immediately respond to those angry customers.
Declining customer loyalty
Customers are sticky within online brokerages. Once brokerages have attracted customers, they tend to stick around: moving money is a pain, and transferring funds between brokerages can take weeks. That fact makes Figure 5 particularly concerning for Fidelity's brand strategists. Upon the August 15 outage, we saw Intent->Loyalty drop to a 2-week low. Intent->Loyalty aggregates loyalty-related keywords that signal customers are happy with your service and are willing to stick around. Falling customer loyalty signals that your clients are leaving your platform, and your brand needs to respond to keep them happy.
Social listening data to inform outages
The Fidelity Investments outage on August 15, 2023, underscored how you can use social listening data as a non-traditional signal for software outages and the potential brand damage they can cause. After collecting and analyzing data from r/FidelityInvestments, we identified key indicators such as a surge in negative sentiment, anomalous post volume, and declining customer loyalty, shedding light that the outage occurred and the significant brand consequences of such disruptions. This experience highlights the importance of swiftly addressing software issues to mitigate brand damage and maintain customer trust in today's competitive digital investing landscape.