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Companies are swimming in data. The amount of customer data they collect is not slowing down. On top of that, every business function wants data to answer questions about the customer experience or function they own.
More companies are seeing their business functions operate independently of one another in collecting data and analyzing it. Teams often create their own surveys or look at only a subset of calls, chats, social media posts, and other customer communications.
But this trend can create an issue of siloed information. Data gets divided, and this often leads to a fragmented representation of the customer experience. Disparate data and teams create disparate customer experiences.
Many brands aren’t aware of enterprise CX analytics, and very few understand the benefits it can provide. The idea is to bring together a brand’s data into a singular analytical view. This is the best way to analyze the customer experience, as it prevents information from being siloed with one team or another. Customers do not view a company as a siloed entity – they view it as a singular brand. Their experience should reflect that outlook.
A truly enterprise CX analytics platform includes all the unstructured data a brand regularly collects, including customer conversations across every channel. Unstructured language data makes up more than 70% of all data in the world, and that number is growing every day.* Nothing provides more insight into how customers experience your brand than conversations. Every interaction with or about your company, regardless of where it happens, should be analyzed.
The impact of enterprise CX analytics cannot be understated. Below are five of the most profound benefits of implementing enterprise CX analytics into a company:
The greatest benefit enterprise CX analytics has to offer is the way it helps companies overcome the inefficiencies that come from siloed data. Collecting multiple types of data is a challenge But just as customers prefer an omnichannel experience, brands should aggregate data across every channel they use, regardless of which business function uses it. Establishing a data foundation that joins data helps ensure a business is looking at the experiences they offer with a consistent lens. With a unified dataset, you can view customers holistically rather than based on the channel or platform they use to interact with your brand. No more arguments about which data source is more accurate; they’ll all be in the same place.
Breaking down data silos also helps brands break down business silos and forces teams to work together. Without silos, work no longer gets shelved between the cracks or kicked around to different owners. Having a single source of truth expedites the entire data collection and customer analysis process. Business functions can begin collaborating sooner on projects — and with a holistic view of the customer, they can better understand how their work impacts other teams. Without an enterprise CX analytics platform, teams often have little to no insight into how their work affects other functions. Customers often voice how their experiences are disjointed and broken, but with an enterprise CX analytics platform, those poor experiences are much easier to tackle, together.
Companies prioritize their work based on the information customers provide; however, it’s easy to make the wrong decision with incomplete information. If you’re missing conversations or data points from your customers, you could be missing your next multi-million dollar priority. Enterprise CX analytics gives business functions the ability to compare their priorities against those of their customers — and because there is a single source of truth, prioritization is no longer based on a myopic survey or a single piece of feedback. Arguments about which initiative needs to be done next can be compared side-by-side with exactly what the customer wants most.
One of the most important technological improvements in the last few years has been the acceleration of Natural Language Processing (NLP). This is now an indispensable tool for CX programs. Of course, the ability to analyze conversational data is not a new capability; however, it was only recently that the technology became accurate enough and accessible enough for business to use at scale. Now, brands can analyze this data in a fraction of the time it took them before.
The most important aspect of any data or insight is its impact on the business. Providing an extensive description of the end to end customer experience, as well as the cause and effect of each action throughout, creates actionable information. Most data provides the results of an experience; actionable data details what is driving those results.
The benefits of enterprise CX analytics are undeniable. Few analytics solutions can inherently force a company to be better at CX. The five items listed above don’t require a lot of work from engineers or IT. Rather, they are the byproduct of having a best-in-class unified platform, like Khoros CX Insights. To learn more about what CX analytics can do for your brand, check out our guide: The Difference Between Customer Experience and Customer Feedback.
*Siegel, Eric (2013) Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die.