How Important is Sentiment Analysis?
Collaboration analytics is an evolving field, with many platforms offering some additional reporting and analysis capabilities. However, these major players currently lack the tools to measure social’s impact on structured collaboration activities – leaving organizations at a disadvantage. To bridge this gap in needed insights, vendors need to up their game; or else companies must develop solutions utilizing existing data sources until suitable options arrive.
Organizations track basic measurements: number of posts, comments, downloads, and number of “Likes,” but we do not take the next step of trying to understand how these statistics affect collaboration. Metrics are the key to driving end user adoption. Unfortunately, collaboration has an analytics gap. Managers who own the success of collaboration across their organizations know this intuitively, yet they rarely go beyond the out-of-the-box data points and leaderboards that come with any social collaboration solution.
There is very little visibility into what people are doing, and much less data on why they are doing it.
If there’s one thing we know to be true, it’s that analytics drives performance. Seeing metrics over time helps us understand if our efforts are producing positive results or if adjustments need to be made for improved outcomes. Knowing you’re being measured often fuels people and teams alike into action – a critical part of any successful engagement strategy is making sure the right metrics are in place as your metric barometer! Evaluating progress means taking regular stock of how things are going and an opportunity refocus on what matters most skillfully measure impactful change.
Metrics and KPIs should be regularly reviewed and optimized. You’ll want to continually refine your analysis, review your data sources, and adjust your metrics to ensure you’re making the right assessments.
You cannot improve what you do not measure.
Creating a Successful Engagement Strategy
The danger with not being able to measure and adequately manage the collaborative activities within the enterprise is that administrators have no way to determine which features, which teams or which collaboration initiatives have been successful. As a result, many organizations will find their end user engagement gains temporary, as users very quickly move past the novelty of anything new if it does not also bring perceived value.
A key to success in enterprise collaboration has been to align collaborative capabilities with specific business activities, and then track the changes over time. An example might be incorporating polling, threaded messaging and ratings systems common in most enterprise collaboration platforms into the product development processes, and then to measure the level of activity before and after adding these capabilities — and their continued usage over time.
The benefit, of course, is that you’re giving the extended team the ability to provide input into the identification and prioritization of features in a company’s product roadmap, but you’ve now also create discrete and measurable collaboration activities that will help your organization better track team involvement (engagement) in the product design and review process.
As you track this over time, you’ll be able to identify sentiment (level of interest) around specific features, or various product releases, as well as an overall trend (downward or upward) of participation.
Adding Sentiment Analysis to your Toolbelt
Sentiment analysis is gaining traction in the workplace as organizations recognize its power to uncover insight from data produced by their collaboration platforms. This kind of sentiment analysis uses natural language processing, text analytics and machine learning algorithms to analyze sentiment data at scale. The sentiment information helps organizations better understand how employees are adopting and engaging with company initiatives, policies, procedures, products, services and much more. With sentiment analysis, companies can gain insights into employee sentiment that they would not be able to get through traditional surveys or feedback forms.
From sentiment scores to sentiment trends over time, sentiment analysis can provide valuable information on how successful internal initiatives are being adopted and used across the organization. Organizations can use this knowledge to adjust strategies or tweak initiatives so that they generate even better outcomes in the future. In short, sentiment analysis is an invaluable tool for organizations looking to maximize the potential of their collaboration platforms. With it, companies can understand not just what’s happening, but why it’s happening and how to act on that knowledge. This kind of sentiment-based data can be a powerful asset when used properly.
Overall, sentiment analysis is a powerful tool that can help organizations make data-driven decisions and better understand the sentiment behind their collaboration platforms. By leveraging sentiment data, companies can maximize the potential of their internal initiatives and optimize adoption within the organization.
In short, sentiment analysis is transforming the way companies use data to drive business outcomes. With sentiment analysis, businesses have more insight than ever into how their employees are responding to initiatives within a collaborative environment. This understanding can be invaluable in helping them determine what works and what doesn’t when it comes to driving employee engagement and delivering successful outcomes.
By understanding sentiment data through sentiment analysis, companies have more insight than ever into how their employees are responding to initiatives within a collaborative environment. It’s clear that sentiment analysis is an increasingly valuable tool for optimizing adoption across business environments and achieving successful outcomes.
References
- “Sentiment Analysis for Collaboration Platforms.” AYLIEN, 2019, https://aylien.com/blog/sentiment-analysis-for-collaboration-platforms/.
- “What Is sentiment analysis?” sentimentanalysis.com, https://www.sentimentanalysis.com/what-is-sentiment-analysis/.
- Smith, Tricia. “7 Ways sentiment analysis can Improve Your Business.” Social Media Today, 15 Mar 2018, https://www.socialmediatoday.com/news/7-ways-sentiment-analysis-can-improve-your-business/518788/.
- Kaushik, Avinash. “Sentiment Analysis: How to Do It Yourself (DIY) & What to Use it For.” Analytics Vidhya, 24 Aug 2017, https://www.analyticsvidhya.com/blog/
