Читать книгу Becoming a Data Head - Alex J. Gutman - Страница 41

You work for a Fortune 10 company, Company X, that recently received negative media attention for a socially insensitive marketing campaign. You've been assigned to a project to monitor “customer perception.”

The project team consists of the following:

 The project manager (you)

 The project sponsor (the person paying for it)

 Two marketing professionals (who don't have data backgrounds)

 A young data scientist (fresh out of college and eager to apply the techniques they learned)

At the kick-off meeting, the project sponsor and data scientist quickly and excitedly discuss something called “sentiment analysis.” The project sponsor heard about it at a recent tech conference after a competing company reported using it. The data scientist volunteered they knew sentiment analysis, having implemented it in their senior capstone project. They think it might be a good technique to apply to customer comments on the company's Twitter and Facebook pages. The marketers understand the technique as being able to interpret people's emotional reactions using social media data, but they don't say much.

The basic premise, you are told, is that sentiment analysis can automatically label a tweet or Facebook post as “positive” or “negative.” For instance, the phrase, “Thank you for sponsoring the Olympics.” is positive, whereas “Horrible customer service” is negative. Conceivably, the data scientist could count the daily totals of positives and negatives, plot the trends over time (and in real time!), and subsequently share the results via a dashboard for all to see. Most important: no one needs to read customer comments anymore. The machine will do it for everyone. So, it's decided. The project kicks off.

A month later, the data scientist proudly shows off Company X's Customer Perception Dashboard. It's updated each day to include the latest data and lists some of the week's “positive” comments along the side. Figure 1.1 zooms in on the main graphic in the dashboard: trendlines of sentiment over time. Only positive and negative values are shown, and most comments are neutral.

The project sponsor loves it. A week later, the dashboard is displayed on a monitor in the break room for all to see.

Success.

Six months later, the break room is renovated, and the monitor is removed.

No one notices.

FIGURE 1.1 Sentiment analysis trends

A postmortem of the project revealed no one in the company used the analysis, not even the marketers on the team. When asked why, the marketers admit they weren't really comfortable with the original analysis. Yes, it was possible to label each communication as positive or negative. But the idea that nobody would need to read comments anymore seemed like wishful thinking. They questioned the degree to which the labeling process had even been useful. Further, they countered that perception couldn't only be measured by online interaction even if that was the dataset most readily available to support sentiment analysis.