When it comes to business intelligence (BI), the more you know, the better off you’ll be in the long run.
Getting to grips with BI
According to Forbes, dashboards, reporting, end-user self-service, advanced visualization and data warehousing are the most important technologies strategic to BI in 2018. The aim? Better decision-making, increased revenue and a sharper competitive edge.
Wait, wait, wait. What?
Okay, we’ll take it one buzzword at a time.
Put simply, BI is research-based information that helps you make informed business decisions. In general you’re talking about data collected from various sources – such as Google Analytics, social media and customer satisfaction scores and surveys – then analyzed and repackaged, making it easier to understand. BI can help you determine exactly how your customers interact with your business, arming you with the tools you need to improve your customer experience (CX) drastically.
‘Analyzing data correctly gives you a clear picture of your customer groups and your product, and indicates how successful your business is and will be in the long term,’ says ZaiLab data analyst Sanneke Brok. ‘Moreover, using statistics and models for your data will help you target the right customer with the right message, set the right pricing strategy and optimize sales and service channels. What businesses need to understand is that analyzing your data continuously is key to adjusting in time to changes.’
How the big guys use BI
Forbes recently published a case study on how coffee giant Starbucks used BI to make strategic direct marketing, sales and business decisions.
What they did was launch a reward program and mobile app, effectively increasing the amount of customer data they were collecting by an additional 30 million users. What they did with this data is quite something.
- Starbucks recorded customers’ buying habits (including coffee preference and time of day of the order) on to their point of sale system, so baristas at any location could identify their customers’ preferred order immediately.
- Customers were also sent personalized offers and discounts based on their individual profiles.
- Using the company’s cloud-based artificial intelligence engine, the app suggested new products according to holiday, location, time of day and weather.
- Targeted emails were sent to customers who hadn’t visited a Starbucks in a while to re-engage them.
- Starbucks used the data to determine which products to launch at grocery stores during their expansion.
Starbucks may be a mega-corp, but using their BI to make data-driven decisions in this way shows us exactly why they’re at the top of their game. Not only do they leave nothing to chance when it comes to big decisions, they also put their customers first in everything they do.
This is a lesson well worth learning.
BI in the contact center
Contact centers basically run on data. Scratch that, they’re made of data. They’re so full of data they’re practically a character in Star Trek: The Next Generation.
BI can give you valuable insight into your day-to-day processes and help you identify factors that are potentially influencing your service levels. We’ll use a couple of scenarios from the Telax whitepaper, Contact Centers: The Secret to Business Intelligence as examples. (Download your copy here.)
The first example shows how BI can be used to change problematic metrics.
Company A looked at their data and realized their best customer satisfaction scores stemmed from longer calls. This was a problem, as their agent performance metric was measured against the speed at which agents handled calls.
They looked deeper into their BI and learned that agents with aggressive call handling times tended to have the greatest number of unresolved inquiries and repeat customer calls. In effect, their performance metrics had inadvertently created a ‘get them in, get them out’ culture and was adversely affecting the customer experience.
Thanks to BI, those at Company A were able to improve their operational processes and fix the holes in their CX.
BI can also be used to identify busier periods in the contact center.
Company B, an insurance company, used contact center reports and metrics to find a link between weather and call volumes. They found that, after heavy snowfall, their call volumes increased by 6%. As a result, they could determine exactly when they would need extra staff to handle increased call volumes.
Our last example illustrates how BI can also be used to improve efficiency.
Company C found that their customer-support agents spent most of their time handling similar issues. They decided to create a tiered support system, freeing up other agents to handle the bulk of calls while dedicated experts tackled the recurring issues that took up most of the other agents’ time.
It all boils down to one point: using the data at your disposal can improve your customer experience and increase efficiency across your entire business. ‘From the moment companies adopt this mindset, a change to a more fact-based way of decision making occurs and drives a customer-centric approach – which pays off in long-term profits,’ says Sanneke.
Want to read more about improving the CX in your business? Try this.