Big Data and Knowledge Management: 5 Ways You Can Benefit

by | Knowledge Management

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Are you struggling to utilize the data collected by your company? Are you wondering how to improve the knowledge your organization manages and actually possibly reap the benefits of processing all this customer data?

You’re not alone. Forbes estimates 95 percent of companies feel the need to deal with unstructured data.

You might not know exactly how to make use of customer data to improve the knowledge (or your product you deliver) to the market—but it’s a task worth taking on. Companies who find ways to utilize large data sets simply make better decisions, deepen relationships with customers, and build a more substantial customer base.

The Netflix example

Take Netflix, for example—a company well known for using customer data. Researchers have estimated Netflix’s recommendation engine saves the company more than 1 billion dollars each year—a number likely higher now than previously reported in 2016. In the case of Netflix, they use data others have previously ignored to feed an algorithm, and ultimately keep subscribers from canceling.

Truth be told, you don’t need a huge team of engineers to use big data in a knowledge management context—you need a knowledge management platform that can collect and use data sources you connect to automate knowledge work and produce recommendations.

In this post, we’ll dive a bit deeper so you can learn how to big data to improve your knowledge management process, and the benefits of doing so.

What is big data in knowledge management?

The phrase “big data” refers to data sets that are very large and complex—too complex to easily process and use. Typically, big data contains information from many different sources and in many different formats.

In the old days, companies took in data slowly and steadily, and there was plenty of time to analyze each set of figures before the next group arrived. Data collected by businesses has now grown so complex that legacy computing tools can’t store and analyze it.

In the case of knowledge management systems, the big data problem continues to plague companies that don’t know what to do with all this raw data. If you use any type of knowledge management software (or several), you likely have tons of data points related to knowledge that can be collected, like:

  • Article views
  • Search queries
  • Feedback
  • Content ratings
  • Favorited content
  • User activity
  • Empty searches

Most knowledge bases (and even platforms) don’t do much with this data, they don’t help companies produce better knowledge, they don’t use algorithms or AI to influence decision making.

To learn about a new breed of knowledge management platforms that use this data to surface better knowledge and automate knowledge work—get your copy of our platform overview guide.

The AI Survival Guide for Knowledge Managers Read this guide to future-proof knowledge management in the age of AI.

5 benefits of big data in knowledge management

Once you have the right KM system (people, process, and technology) in place, your organization can actually realize the benefits of big data to produce higher-quality knowledge and better decisions. With the right knowledge solution in place, here are a few of these data-related benefits to expect.

1Higher-quality knowledge across the board

Your internal teams or front line agents want to ensure the information they access is up to date, that information is reliable. Knowledge management platforms that utilize data from content ratings (like thumbs up/thumbs down data) will add visibility to content that needs to be fine-tuned.

Over time, your company’s content creators can improve poorly rated content, and knowledge managers will maintain a healthier, more up to date knowledge based on real data from content consumers.

If knowledge managers simply have a KM platform that can identify content optimizations automatically (by using content-specific data points), they can then act on this information; the end result: better answers for everyone over time.

2Data-driven decision making

It’s a safe bet that you hear a lot about the concept of “data-driven decisions.” But it’s worth noting that not all data-driven decisions are created equal. The best decisions stem from actually using a wide range of data. Not just one narrow data set, data from different channels, even different departments.

Your knowledge management strategy should incorporate as many data points as you can process and make sense of with the knowledge management software you use. Data you can get from integrating into contact center platforms and other third party apps is valuable data that can be interpreted, data you can act on to make knowledge better.

Instead of managing all your customer data in silos, centralize it into a central knowledge management platform that people and algorithms can access to make smart decisions.

Any good KM solution should be able to report on content your customers frequently view (or don’t use at all) and help department leaders gain insight into customers.

With the right solution you can use big data to tell a story about your knowledge resources, give employees insight into what works, and ultimately give your company an edge over competitors that may use a simple knowledge base (without these features).

3Valuable insight to help retain customers

Your customer acquisition and retention metrics are paramount to a successful business; for B2C companies that have tons of data, you should use it wherever possible.

You can harness data from a variety of sources to improve knowledge—whether that’s sentiment analysis from social media platforms, comments on requested features, tutorials or features, even negative reviews online.

The key is finding a way to pinpoint and analyze the data points that can help you improve the knowledge your customers consume. Big Data—especially used in the context of a knowledge management platform— is cost-effective and often more telling than a customer survey or focus groups.

KM platforms give your teams immediate insights into what customers actually think about your content, services, and products—wherever this data comes from. The more you know about what they’re looking for, the easier it becomes to attract new customers and keep existing ones.

4Faster answers and a better experience for customers

Customers want fast, accurate information at the tip of their fingers — and they wanted it yesterday. If your business can meet consumer expectations, you’ll be well-positioned to increase your customer base and build strong loyalty to your brand.

Think about any content recommendation engine. These algorithms rely on big data—tons of data points from customer interactions—to surface the best recommendations possible.The more valuable data you can provide, the easier it will be to deliver a recommendation a customer finds useful.

Unlike other platforms that don’t connect to big data sources (or do anything with this data), a modern KM platform like Shelf can use this data to both generate recommendations to content creators, as well as improve a customer’s experience in a customer service environment.

For example, when a customer has a question, Answer Assist (a key knowledge management component) can process the query and return an answer to agents or customers. Since the KM platform acts as the hub for such a vast array of data, it can also use data from previous interactions to deliver the best answer.

In more ways than one, big data fuels the products (like Answer Assist) that make it easy for live agents to answer customers’ questions in a thorough and timely manner.

5Ability to use customer data like intent signals

All too often, businesses sit on stockpiles of data that simply do not get utilized. One of the great strengths of a knowledge management system is its ability to process all intent signals—data like empty searches and other data that typically gets ignored.
What separates any other knowledge based or platform from a knowledge automation platform is the ability to access data and use it to automate work!

Here are a few sources of this intent data you might already be collecting:

  • Data from web portals
  • Chatbot data
  • Voice transcription data
  • Data from help portals and ticketing systems
  • Data provided to an IVR

Even though you may not be using or capturing data that customers provide directly to your agents (or in other places), consider this exercise a knowledge management best practice; if you truly want every piece of published knowledge to resonate with an audience, you need a tool to interpret this information.

Need more out of your knowledge management solution?

Instead of viewing big data as an overwhelming initiative, first assess your current knowledge management strategy. Your main source of truth for knowledge should have the ability to collect and process tons of data from channels you depend on—whether that’s a CRM, CCaaS platform, or website FAQs customers frequent.

The right knowledge solution will enable your knowledge team to actually leverage data you already collect and use it to deliver on-target, accurate information to consumers or employees. So much valuable data gets generated every single day—are you prepared to take advantage of it all?

Read this Next

A Buyer’s Guide for Smarter Knowledge Management

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