What I am Hearing Part 4

Today, we are going to talk about the role of enforcement in the world of customer service and specifically what I am hearing in the communications market place about how they are dealing with enforcement.

Enforcement can mean different things to different people when it comes to customer service. For some people enforcement revolves around the need to enforce certain policies or guidelines in order to meet a legal requirement for the company. For others, the idea of enforcement focuses in on meeting certain handle time metrics or FCR metrics. Still yet for others, the idea of enforcement is really all about the scripting of interactions to ensure proper outcomes.

Recently, I have been hearing from communications companies that they are primarily focused on three things when it comes to enforcement: Credits/Adjustments, Required Call Components and Tech Support Call Flows. Lets tackle each in a bit more depth.

1. CREDITS AND ADJUSTMENTS

A number of companies in the communications space, in particular the wireless companies, are taking extra time to focus on the roles of Credits and Adjustments in their company. The premise behind these credits and adjustments is simple, there are times when companies enable their customer service leaders and team members to compensate a customer for an issue they have had by crediting their bill or making an adjustment to their service in some way. I was talking with a wireless company recently and they told me that they set aside around $100 million dollars a year to allow their teams to make credits and adjustments. So, there is a lot of money at stake.

Now that I have given you a sense for the size of the problem, there seem to be two challenges that companies are facing.

The first is ensuring that customer service personal are making the right decisions about when to give a credit or adjustment. Not everyone will understand or remember the correct process for every type of credit or adjustment that might be faced when talking to a customer. In this case, companies are looking into call flow software that can help enable their representatives to make the right decisions about next steps for a given customer scenario.

The second challenge with credits and adjustments is ensuring that the customer service teams are using the alloted pool of money wisely. In some situations, billing systems are intelligent enough to know what is the correct amount of money to credit or adjust based on rules that are set up in that software. But other times, specifically in cases where the credit is a goodwill credit, a person may not know what the "right" amount of money might be to give away to secure the relationship with the customer. Some companies give maximum flexibility to their customer service teams to make the right call, others restrict their teams to only certain dollar amounts without chain of command stepping in to approve. I am hearing more and more from companies that they would like to solve this problem with some type of enforcement engine that would make suggestions to their teams that take into consideration what is best both for the customer, based on lifetime value etc, and what is best for the company.

2. REQUIRED CALL COMPONENTS

Many companies are trying to understand how to best address the needs of legal, while at the same time not overburdening their customer service teams and customers with paragraphs of disclaimers or legal jargon. A great example of this came from a customer of mine that was struggling with a lawsuit that had been brought against them because a customer had called up complaining about charges they had received at installation of their service. The customer disputed what they had originally signed up for with the agent on the phone and then sued the company because they believed they should not have been charged.

In the case of my customer, they had some recording evidence they could go back to in order to prove that they were not in the wrong and the customer had indeed agreed to the order and installation charges. But, the company still realized that they needed a better way of being able to enforce and reinforce the legal language to ensure that they were protected in cases like this.

Many other companies I have talked to recently are also struggling with this same challenge and are investigating options that will help them better enforce, both timing of and content of, legal disclosures that need to be provided to their end user customers.

3. TECH SUPPORT

As we all know, communications companies are getting more calls than ever for tech support. We addressed this in the first post of this series, but would like to mention here as well as an important dialog that is going on in terms of enforcement.

Probably the biggest single challenge that tech support/oss support faces for communication companies is making sure that folks that are in tech support follow an appropriate process before either making a refund, sending out a refurbished device or rolling a truck to a house. This is always a tricky one to balance because of the typical experience level or tenure of tech support reps. They tend to be longer tenured folks and tend to believe that they have seen most of the problems that come in and know how to deal with them. That may be true, but what companies are still trying to deal with is that you can't depend on that person being their forever and when they go, that knowledge goes with them. So, the question that keeps coming up in my meetings is, how do I make sure that my tech support reps are following a process that is consistent, leads to fewer refunds or truck rolls and allows me to replace service reps relatively painlessly when they decide to leave the company?

Enforcement can be a real challenge for a variety of technology and human reasons. Sometimes it is just a human being wanting to exercise more control of the situation or sometimes it is a matter of the technology not being flexible enough to help create enforcement in the variety of situations that leaders need to address. None the less, these issues around enforcement are top of mind right now with companies in the communications space and they are actively trying to find solutions to the challenges that are presented.

Podcast Interview

I was recently asked to give an interview for a conference I am attending later this month in Orlando. I gave them a few thoughts I have on some of the things that are interesting in the customer service space. Please check it out, but make sure you turn up the volume as they have some recording issues.

http://www.iirusa.com/upload/wysiwyg/2010-M-Div/M2300/RobSader_NACCM.mp3

What I am Hearing Part 3

Ok, so here we are in part three of the series on what I am hearing in the communication service provider space. In the last week and a half, we have talked about how many companies are starting to focus on Offer Management and process enablers in order to make an impact in their service organizations. Today, we are going to tackle the issue of Intelligent Decision Making and it's impact on customer service.

The foundation around this particular post comes from a number of conversations I have been having lately about data and how using data or capturing data can be both a blessing and a curse. It can be a blessing because having boat loads of data can help people make better decisions, no real argument from most on this point. Not rocket science either. But data can also be a curse in the sense that many companies are swimming in data and can be bogged down in making decisions because of the enormous amounts of data in their Enterprise Data Warehouse.

There is also consideration made for data that is real time and data that is static. Companies are trying to understand how both types can be used to further the needs of the business and customers.

Again, after a number of different conversations, it is becoming more and more clear that companies are starting to depend on software to help make decisions for them. I know that it seems all to Tom Cruiseish from Minority Report, but companies are starting depend more and more on new types of software to help them not just make sense of data statically and make forward looking decisions. They are looking to software to help them make real time decisions about servicing their customers.

A great example of this is in the retention space for communications service providers. As we have been going through this downturn in the economy, there obviously becomes a focus on the existing customer base ensuring that churn rates are as low as possible. For years companies and specifically marketing departments have been using data that can be gathered about customers usage patterns, geography, competitive market etc, to create offers and present offers to customers to ensure they stay a customer. The challenge that companies have had in this regard is that they are using very static information to make offers or to try to save customers, they aren't using dynamic real time information to make the best offer to that customer. In the case of someone calling to say they are cancelling, their may be three reasons the customer gives the call center agent as to why they are cancelling: a new competitive offer, a service issue they are having currently and the first agent they spoke to was very rude to them. In a large majority of service organizations, that data is not used in an intelligent way to help agents make decisions about how best to care for and save this customer.

So what I see happening in the market is that companies are starting to use Real Time Decisioning engines to help make the most effective pitch or offer to save that customer that we described in the example above. These engines are able to take the static information or data that is available about the customer, combine it with some real time data input about what is happening in the moment with the customer on the phone and help pull together an offer that will be much more specific and thus much more likely for a customer to say yes to.

There seem to be a couple of keys in choosing these types of engines that are important to the people I have been talking with over the last several months:

1. Flexible- The Real Time Decisioning Engine that is selected needs to be flexible in a couple of different ways. First, it needs to be able to accept inputs from a variety of different points in order to make the best decision possible. Not only should it accept inputs from back end systems that will feed it static info about the customer and their history with the company, but it should also be able to accept input from people in real time so that the decision that is made is as accurate as possible. Second, the engine should be flexible in it's deployment model. It should not take you a year and buckets of money to deploy these engines. They are complex, but at the same time they should be flexible enough to start small and grow with the needs of the business. A SaaS solution or Cloud based solution may be a great option here.

2. Dynamic- The engine itself should be easy to use and dynamic enough so that if marketing makes changes to offers or programs, the decision engine can be changed within minutes to reflect the updated inputs from marketing. It should not be a situation where you need to call in the vendor in order to make big, expensive code changes in order to accommodate tweeks in data inputs.

3. Learning- Probably the most important criteria that needs to be considered is the ability for the engine to learn from decisions that are suggested and made. As the business changes, as the customers change, as the macro economic environment changes, you want the engine to be able to learn from what decisions were made and be able to make smarter or more effective decisions next time around. As an example, when a customer calls in and cancels and they happen to be from Chicago, are in a competitive area, have had 4 service calls in the last 2 months, are very upset, are referencing an offer from a competitor and have been loyal to you for 5 years, you want to ensure that the engine learns by making changes to the offer next time they see a customer with the same characteristics as the customer that was just lost. The idea is that the company should be learning every time they lose or win and thus really using the data they have in real time to make better decisions for the business.

There are only one or two companies that I know of right now that have successfully rolled out Real Time Decision Making software to their users. But, I have heard from a number of companies that they are starting to dig deeper and learn more about how it will be useful for them. Some companies see the value by helping to retain more customers. Some see it as a way to help agents make better decisions about who to give credits or adjustments to. Some see it as a way to enable sales agents to close more sales. In the end it is all about taking decision making into real time.

The take home message is that there is software starting to come into the market that can help companies make better real time decisions about their customers and their business. It can help them save more customers, differentiate in the treatment of customers, ensure credit or adjustment policies are adhered to and a variety of other specific customer service issues. The key to success for companies will be in taking baby steps to using this technology, ensuring success through small projects and then growing it to be more useful across the service organization.

Push vs Pull

I am going to be adding one more set of learnings to my series on What I am Hearing. This idea of pushing information versus pulling information. Seems relatively mundane or simple, but there seems to be an interesting dialog happening right now about this concept. Likely coming from the changes in the consumer market, but none the less, still an important dialog that needs to be explored.

Next week will be part 3 and 4 of the series.