Ever since the global interest in augmented analytics (the use of machine learning and natural language processing to enhance data analytics, data sharing and business intelligence) started rising, sales and business development teams have turned their minds to it, too. However, many organizations remain unsure about how to successfully integrate it to achieve tangible results.
Here I will share my answers to some of the frequently asked questions we get from our clients about deploying augmented analytics solutions for their business development teams.
Defining Augmented Analytics
Augmented analytics is an umbrella term for technologies that automate data research and analysis and give the human analysts valuable business insights. These insights can aid in a variety of business functions, from identifying prospects to decision-making about deals.
But why can’t humans find these insights, you might ask? They can, but only to a certain extent. The main selling point of augmented analytics is that it streamlines the process for business users, which makes it easier for them to get and apply the results they need faster.
For example, if the analytical team previously spent 70% of their time on collecting and correlating data and 30% on analyzing it, augmented analytics could take over that 70% and free up the rest of the time for the team to dig for valuable insights.
So, how does this process work? Augmented analytics can best be broken down into three aspects: machine learning (ML), natural language processing (NLP) and automated insights (the end result).
Machine learning: For example, if you are trying to decide on the best pricing strategy for your service, you can use ML algorithms to automatically examine your competitors’ offers and your customer relationship history and suggest an appropriate price for a particular customer.
Natural language processing: NLP is a conversational AI technology that allows human data analysts to query the data and interact with it using natural language -- either in text or voice form.
These features have given rise to so-called self-service analytics. It has already found its way into platforms such as Oracle Analytics Cloud, IBM Cognos Analytics, and SAP Analytics Cloud, to name just a few.
Automated insights: Here, the technology draws together ML and NLP so that system users can get the answers they need faster. For example, your sales team could ask, “What are the growth projections for Q1 2020?” and receive a visualized answer.
How Can You Use Augmented Analytics To Boost Business?
Theory is all well and grand, but how can you use these technologies to influence your business? Let’s take a look at some of the ways you can use augmented analytics to allow faster action and boost sales, customer satisfaction and business processes.
Knowing Your Customer Base Better
Augmented analytics empowers your data analysts to evaluate large quantities of information systematically and can give them feedback about current and potential customers. This allows you to profile your present and prospective customers and gives your outward-facing sales teams insight into which prospects are most valuable.
For example, by analyzing customers' interaction and purchasing history and projecting it onto prospects within the same granular segment, you could forecast expected demand and get better prepared to meet it.
Coming Up With Proactive Recommendations
It’s not unusual for a customer to approach a business with only a vague idea of what exactly they need. In these scenarios, the sales team can use augmented analytics to quickly evaluate the request and understand how it fits into their company’s offering; both the business and its prospective customers can avoid wasting time and money.
Sales data is instrumental here. By sifting through sales history, including failed and curtailed deals, and mapping it out by customer personas, sales managers can take what works and leave out what doesn't to maximize the likelihood of a win.
Quickly Adapting Your Services To Supply And Demand
Market analysis takes time and energy, and it can be difficult to predict market trends and changes. Employing augmented analytics in your business strategy can help you identify potential marketwide trends before they happen; for example, there might be an uptick in blockchain systems or a renewed interest in enterprise IoT. For this purpose, it makes sense to look at the seas of online information found in digital mass media, public discussions, reviews and social networks to identify the trajectory of your audience's expectations. This can help your company offer more relevant services, identify new markets, gain the first-mover advantage and ensure you're making the correct hiring decisions.
Moving Forward With Research And Development
Augmented analytics can help inform you of future developments in your organization’s niche. This can allow you to effectively allocate resources to specific areas of research and development to stay ahead of the competition. Here, you can use ML-powered models to test your product development hypotheses based on vast historical, demographical and location-specific data. Combined with the market analysis we touched upon earlier, this strategy can help you identify new avenues for growth.
How To Introduce Augmented Analytics To Your Team Successfully
Once you decide that augmented analytics is a step in the right direction, the next thing to consider is usually how to get it to work for your company.
As with any other business decision, it’s vital that you introduce this technology with care and in response to direct business requirements. Defining your business goals and the success criteria for your future augmented analytics system are sound strategic steps that can help make your implementation well-paced and predictable.
Another step I advise taking is to work toward positive user buy-in. As I’ve seen so often in our enterprise clients’ software adoption initiatives, employees can perceive any kind of automation in the workplace as a threat. To mitigate this, it’s important to set up a straightforward software onboarding timeline and procedure to make the entire process as stress-free as possible for the end business users.
