A wealth of data to be found in the customer contact center
Business intelligence (BI) remains an unknown and ambiguous concept to most resources within the different levels of a customer contact center.
On September 27th, LOEM held a conference on this topic during its exclusive annual event for customer contact centers. The primary goal was to take stock of current situations and show the benefits that business intelligence could offer.
What is business intelligence (BI)?
In 1958, IBM defined business intelligence as follows: “The ability to grasp the interrelationship between current facts, so as to guide them toward a desired goal.”
Then in 1989, Gartner described it as “concepts and methods for improving decision-making, based on facts from a support system.”
In 2008, David Buckingham, an expert in Big Data, found the definition of business intelligence that is perhaps the most accurate.
The latter is what best represents business intelligence for LOEM. Oil is a rare commodity that, once transformed, generates profits.
The Era of Data
We are in an era where data is accessible everywhere, at any time. It is therefore possible to know the specific needs of our customers and take the time to properly analyze their buying behavior. To accomplish this, it is our responsibility to use the data that emerges to build a relevant corporate culture.
Currently, the world produces, in two days, more data than it produced between the beginning of humanity and 2003. Approximately 2.7 trillion terabytes of data exist in the digital universe and the amount of data collected by organizations doubles every 14 months.
How does business intelligence work?
Business intelligence is about taking all the customer data, collecting it to one place, sorting it, and then merging it to analyze the results using powerful algorithms that make it profitable information. The goal is to target the needs of customers and to define the different personas of the company.
What is a persona and why is it relevant to BI?
We are all different, but customers are all the same. The personas correspond to the buyer profile. Defining customer data sheets makes it possible to adapt products / services to meet the needs and expectations of customers. These profiles are defined by an organization’s marketing team and include the following:
- Their job and their passion
- The typical day of your client
- Their problem
- Their motivation
- Their consumption
- Their experience
The majority of organizations have a dedicated team responsible for business intelligence. This team manages the millions of data stored in the various databases, which can then be manipulated. The users can share some of this information. They can also produce analysis for statistical purposes, all with the goal of getting to know their client.
Excel and business intelligence: a toxic relationship
Data files are often created in an Excel spreadsheet. Did you know that the average time to create the Excel file is just over 2.5 days?
The Data Warehouse Institute (TDWI) conducted a study to analyze how organizations produce their data. As of today, nearly 70% of companies still use Excel files to produce their data and the average number of frequently edited files amounts to 837 files per company!
Organizations should consider maximizing their potential by using a minimum number of technology tools, such as a CRM (Customer Relationship Management Tool) and dashboard (which draws data from across the organization).
Man in incapable of pushing the limits of data analysis as quickly and accurately as technology can. In particular, business intelligence tools are needed to define your personas, in addition to starting the transition from, and reducing the use of, Excel.
The link between business intelligence and the customer contact center
By reading and analyzing the studies on this subject, it is interesting to ask questions about the impact of customer contact centers and the link with business intelligence: 80% of organizations to this day have not yet integrated their contact center data into their business intelligence database. And yet the voices of the customers are available with all their experiences, their worries, their problems and their motivations.
The customer experience, a customer’s lifestyle, along with the specific journey taken to contact an organization, contributes to the business intelligence of the customer contact center. However, contact centers are currently only analyzing 1 to 2% of their contacts monthly.
The perfect recipe
When comparing data to oil (as explained by David Buckingham), the contact center has the perfect recipe for producing it and thereby generating profits for the organization. Would you be satisfied to only use 2% of the oil from your well?
It’s time to integrate this wealth with your databases, to truly get to know your customer. You will be able to convert all the opportunities that were previously unknown, prior to the advent of this technology.
By analyzing or listening to only 2% of the contacts, the impact is limited to supporting agents with continued education and coaching. However, this is not enough to improve the relationship with the customer or perform detailed analytics, as well as being able to recognize trends.
The costs of listening to calls within an organization are not insignificant. To be able to listen to 1% of the calls in a contact center that receives 1.5 million calls a year, would require assigning more than 3 full-time resources to the task.
A business intelligence tool now allows contact centers to analyze 100% of the call recordings: the voice analytics tool. This tool, which is linked to call recording, would do the work of 300 quality assurance analysts, from our previous example. More importantly, it would filter all your calls and get out the items that are most valuable to you.
Keyword searches of all calls on days “x” or “y” would quickly give you the trends for the coming days or weeks. A good keyword search analysis would also allow you to better forecast and turn contacts into opportunities. Become proactive rather than reactive!
A voice analytics tool would allow you to analyze first-call resolution problems, to identify all calls in which a phrase such as “called yesterday” was said. You could also search for instances where multiple calls were made by the same number in order to analyze and discover problematic procedures or behaviors. A search could also be done on the most frequent reasons for calls in order to assess the possibility of answering these questions directly in the IVR.
How much money could you save per year if you decided to attack repeated calls in order to reduce their quantity? For a customer contact center receiving 20,000 calls a week, reducing repeat calls by 5% would save $382,720 a year.
Beyond the tools available to the contact center, you must take into consideration the richness of the data and the information collected from the customers who find their way to you. You will discover the voices, needs, preferences and experiences of your customers. Placing an importance and value on the data gathered will turn them into real opportunities.
Well composed teams
In the modern age, it is not enough to only have business intelligence teams. It is also necessary to have at least one resource dedicated to analytics, to be the link between the internal teams of the organization. Communication between departments will be the key to your success.
The business intelligence team should be part of your expertise center, which deals with workforce planning, since contact forecasts form the foundation of the analysis. You can then integrate multiple cross-data analysis to refine your models and be able to better plan for your agents, all while keeping your customers happy.
If you still do not have a business intelligence team, here are the steps to follow to implement it in your organization:
- Determine who is responsible
- Assign leaders to the BI project
- Creation of a Project Management Committee
- Determine the tasks of each member responsible for the project
- Collection of Information
- Collect all relevant files
- Collect databases and other information that must be part of the BI project
- Analysis of information
- Analyze the data collected
- Create a data integration schedule (by step)
- Choose, Integrate, and use the tools
- Integrate data into automated BI tools
- Create custom dashboards for each department.
Your business data is worthless if it is not used the right way. There is oil sleeping in the wells of your multiple databases. Tap into it!
 Gartner Research and “The Bumper Book of Business Intelligence” written by Matillion Business Intelligence