Check more about this interview series

5 – Winning!  The Payback.                   

In the 2002 movie, The Minority Report, Steven Spielberg shows us what mass personalization advertising will look like in the year 2054.  John Anderton (played by Tom Cruise) walks through the concourse of a building where cameras perform a retinal scan of all passersby.  In real time, the “intelligence” behind the cameras is supposedly matching the scan with John’s profile, accessing and sifting through archives of Big Data and based upon this store of intelligence, advertisements customized to John are presented on screens – it even somehow seems to understand that John is stressed and presents an advertisement suggesting a vacation is in order.

Well, it’s not 2054 and of course this is Hollywood [besides, this portrayal seems to me to be more mass confusion than mass personalization].   Notwithstanding this, it’s not difficult to imagine the mass personalization and predictive nature in which companies will engage and interact with consumers, perhaps not in the brazen manner depicted in the movie.  If you spend any time on the Internet, then you’ll know that in fact this is happening today.

In the call center, it’s Interaction Analytics that is processing and understanding large volumes of data (aka Big Data) and in turn, providing the intelligence upon which to take action.

So where is the payback?  Well this is the exciting part because Interaction Analytics is not just about optimizing agents, which in itself can justify the costs of deploying the technology, but it can also help drive revenues.

If you remember in a previous installment of this series, Gartner Group found that companies typically spend ten percent of their revenues on marketing.  What’s startling is that VisionEdge Marketing reports that 84% of marketers cannot report and measure the contribution of their programs to their business.  Marketing organizations can elevate this spend by having the volumes of your call center’s customer interactions mined for actionable market intelligence contained therein.  This invaluable information will help your Marketing organization anticipate market trends, gain insight into the reasons for campaign successes or failures, the competitive climate and of course understand customer needs and wants so that they can then better drive Customer Effort and Net Promoter metrics thereby creating long-lasting customer loyalty and ultimately bolstering Customer Lifetime Value.

As with what typically elicits budget dollars in call centers and as touched upon above, Interaction Analytics also offers significant operational efficiencies resulting from reduced handle times, reduced transfers/escalations, increased first call/contact resolution and call avoidance.  For instance, by analyzing recordings a wireless company can identify that the root cause for a recent spike in hold times, call transfers and escalations was the result of a gap in training on a specific promotion for a roaming package.  A retailer uncovers that the root cause for a surge in the call center is the result of confusing information about a promotion appearing on their web page.  An insurance company can identify that the reason a sales promotion combining home and car coverage for seniors is not meeting expected sales targets is because a competitor is offering a better promotion.  In each case, Interaction Analytics is providing actionable intelligence.

In addition to the above, Interaction Analytics can also automate quality management and compliance functions.  For years, companies have employed quality monitoring tools to identify agent development opportunities and/or non-adhering interactions.  Unfortunately, the ability to uncover those opportunities were limited due to the small sample of calls analysts were able to review.   To address this limitation, some Interactions Analytics vendors have recently introduced automated scoring, facilitating a more statistically valid representation of the quality of or non-complying service being delivered and consequently identifying training opportunities that would have otherwise not been found.

As I mentioned in a previous installment, at an annual growth rate of over 20%, Interaction Analytics is no longer about differentiating your company – Interaction Analytics will be ubiquitous and those not already planning to implement Interaction Analytics within the next couple of budget cycles are planning to become irrelevant.

In closing, this series was written to provide some insight into how Interaction Analytics will play an important role in the call centers of successful companies; hopefully you found it useful. I look forward to any feedback and the opportunity to continue the discussion.  Of course, if you have any questions or want to discuss your call center’s Interaction Analytics plans, you can call me directly at +1 (905) 595-5304; email me at nickf@xentrax1.wpengine.com; or message me directly via twitter at @NickFlaminio.

4 – Navigating Common Landmines

While there are a wealth of benefits, crossing multiple compliance, optimization and revenue generating metrics that justify the deployment of Interaction Analytics – which we will discuss in the next part of this series – there are also ample examples of failed deployments from which we can learn from and plan to avoid so that we can realize those benefits.  There are three common missteps that I want to highlight:

• A failure to understand and adhere to the project’s strategic objective – Understanding and adhering to the project’s strategy is such an obvious facet to success in any business endeavor that it amazes me how frequently the failure to do so occurs. Everyone goes into these initiatives with good intentions, but somewhere along the road and for many different reasons, the project strays from its strategic objective.   Keep in mind when I say project, I’m not limiting my definition to the time in which the actual implementation of this technology begins – I’m also including the discovery stage.  Often times the project has fallen off the rails even before a product has been selected.
• Purchase decision is made because it is a throw in as part of a WFO Suite – All Interaction Analytics solutions are not alike and the benefits to selecting the right solution heavily outweighs the consequences of making a decision that is based on simplifying the procurement and administration.
• No dedicated and qualified Analyst Team planned or in place – While an exciting advance in technology, it’s not magic. Failure to budget dollars that include a qualified team of Analysts is a non-starter.  Don’t hand the application over to your QA team unless they demonstrate analytical skills and are properly trained.  It’s imperative that you budget qualified analysts who not only understand your business but also have the skills to uncover, track and correlate trends, and are able to understand and accurately demonstrate the meaning behind the data (what the data is saying).

The above are just three potential impediments to successfully implementing Interaction Analytics in your call center but there are more.  Where at all possible, I strongly recommend that you reach out to and consult with some of those early adopters – both those that were successful and those that have failed to understand the reasons for their outcomes.

One other consideration – because the application crosses multiple lines of business (Customer Service, Sales, Marketing, Operations), it may be enticing to bring in other lines of business to share in the budget spend.  However, depending upon the structure and culture of your organization, you may want to avoid this as it can easily result in muddled objectives and delay the initiative.  I would certainly recommend consulting other lines of business and make the appropriate considerations in your business case, and where there is no conflict with or weakens the Center’s objectives, choose a solution that will scale in support of these objectives down the road.

Additionally, I would also strongly recommend that you target a single channel for the initial deployment.  In most cases, telephone calls are the most predominant call center interaction and I would consider initially implementing speech analytics; let it soak, then measure the outcomes and adjust any shortcomings before expanding the solution to other channels.  This is not to say that you should minimize other electronic channels in your evaluation of solutions, as current trends suggest, the volumes of interactions from these channels will increase in the years to come and you need to ensure that any solution you implement today, will seamlessly and transparently support them.

In our next and final installment we explain where the return on the investment will be.  We will discuss which key performance Indices Interaction Analytics will power to drive revenue and operational efficiencies.

3 – Cracking the Code

In the previous installment of this series, we talked about how the data in itself is not the answer.  We also need to be able uncover intelligent, actionable meaning from this data.  We know that we capture volumes and volumes of data and that data is captured different ways and in an unstructured format – consequently the mining is not easy.

But as they say, anything worthwhile is never easy.

Only the power of computing can process the vast amounts of data being stored while at the same time, what is required is the ability to derive meaning from data stored in a human friendly format fo https://xentrax.com/part-1-of-our-2-part-series-an-interview-with-nick-flaminio/

This is where the power of Natural Language Processing (NLP) capabilities and Speech Engines found in today’s Analytics solutions are proving to be the key to cracking the code.  As defined in my prior installment, human friendly format includes telephone calls into the call center, as well as other electronic channels such as email, chat, SMS etc.https://xentrax.com/part-1-of-our-2-part-series-an-interview-with-nick-flaminio/ Together, NLP and Speech Engines are enabling machines to better understand the ways in which humans communicate.

While more and more consumers are choosing alternative channels, telephone calls are still the single most popular method of communications in the call center and if you’re recording these calls, there is veritable gold mine on information in those recordings.  The performance Speech Engines have seen a dramatic improvement in accuracy, and there is no reason to believe that this trend will slow down anytime soon.

But not all Speech Engines are the same.  They can be divided into one of two types – Phonetics and Transcription Based Engines.  Phonetics Based solutions search for a sequence of phonemes (sounds) while Transcription based solutions employ text based search methods.  Each having their use-cases and inherent pros and cons.  Regardless of the method, the best solution for your Company will depend upon the business problem it’s intended to resolve.

Because alternative channels are quickly catching up to telephone calls in popularity, it’s also important to ensure the analytics solution you select for your center will scale in support of these alternative channels seamlessly as the customer experience includes every interaction they have with your company.  Just like your customers expect to be able to seamlessly move from channel to channel, you should expect your analytics solution to seamlessly process all your interactions regardless of channels, format or integration in a seamless and transparent manner.

Consumers are choosing to interact with companies in ways that are disrupting conventional service delivery and this is presenting an exciting opportunity for call center professionals to play a more critical role in the success of their company.  Analytics Software will prove to be the most indispensable technology in understanding the voice of the customer for years to come – according to a study by market research company Market and Market published in April 2016, it is expected that the annual growth rate for Speech Analytics will be 22% in the next three years.  We are no longer in the early adaptor stage for this technology; it’s no longer about trying to differentiate yourself, it’s now about being relevant.

Just so there is no confusion, Interaction Analytics Software does not radiate magic properties as many early adaptors can attest to.  There are lessons that can and should be learned from early implementations.  In the next segment, we will discuss some of the lessons learned and how to prepare for success.

2 – Mining for Gold

According to Gartner Research Study, companies will spend approximately ten percent of their revenues on marketing.  That’s a significant spend, but do we know how effective this has been?  John Wanamaker, an American merchant and pioneer in developing Department Store retailing from the late 19^th century, famously said that “half of the money I spend on advertising is wasted, the trouble is I don’t know which half.”

In the first installment of this series, we discussed the expanse of information available to your company about your customer – aka, Big Data in the Call Center.  We know that data is the key, but data itself is not the answer.  We need to understand what all this data is telling us about our customers.  To this end, in this installment we’re going to explore the challenges in mining the data for meaning.

There was a day when merchants were able to have a direct relationship with their customers and they knew everything about them.  What their individual needs were.  What their wants were.  This educated their decisions on everything from how each individual should be serviced, to what products to stock.  As merchants began to expand and open multiple stores nationally, the relationship between the merchant owner and the customer ended and personal service suffered.

With the advent of computers and the database, companies began to accrue information about their customers.  Companies deployed IVR and CRM applications to collect information, albeit very limited, and stored that information in searchable fields.  This type of data is referred to as structured data or “machine friendly” information.  While this information was helpful those fields only contained information companies felt they needed to collect – they were pre-determined fields by someone in your Company.  The value of this data is questionable in that it’s not necessarily what your customers want you know; or perhaps it may have been relevant when they were created, but is no longer today.

Today, there is a plethora of information stored electronically in the recorded interactions between your customers and your call center agents.  There is another radical transformation that is happening in our industry.  Customers are expecting to be able to interact with you in the channel of their choice and at the time of their choice.  Further, your customers are expecting a seamless and agile [omnichannel] experience between the channels.  Companies are responding by deploying different technologies to facilitate better customer experiences across multiple channels.

This new reality introduces a greater complexity as we need to connect the data – I’ll say again, large volumes of data – being captured across the disparate channels/technologies.  In order to truly understand the customer experience, we need to piece together the customer’s journey through all these channels.  Further, unlike the data you have in your database, this information is not stored in convenient rows and columns – this data is unstructured or in a format that’s “human friendly.”  There is no index in which traditional database engines can fulfill queries.

So where are we?  We know that there is a lot of good information about our customers in our electronic interactions with them.  We know that data is key and that we have that data – large volumes of data, captured by disparate technologies in an unstructured format.  Data itself is not the answer.  We also need to be able to discern intelligent, actionable meaning – the Gold – from this data.

In the next installment, we’ll look for answers.

Since its inception, the call center has been considered a cost center. 

This is evidenced by the metrics that have been used in the past to measure success.  In fact, the whole purpose for creating the Automatic Call Distributor (ACD) was driven by the need to reduce, or at the very least control, costs – unless you believe that waiting in a queue before being served is an advancement in customer service.   

Since the emergence of the call center, companies have looked more favorably on projects that showed a clear case for reducing costs.  Sure, there are exceptions, but company executives have widely regarded the call center as a cost center.

There is however, a radical transformation occurring in service delivery, and it’s being facilitated by the emergence of new technology.  In this five part series, we’re going to explore what may be the most dramatic development in service delivery since the ACD.

1 – By the Numbers

In our first of a five part series, we look at the call center industry, and make sense of its size and breadth. It’s important to know the numbers so that we can better understand the significance of the opportunity that exists.

While information on the volume of call center interactions is scarce, we know – courtesy of the US based ContactBabel report in 2015 (US Contact Centers in 2015: The State of the Industry & Technology Penetration) – that there were about 44,000 call centers in the US staffing over 3.4 million positions as of 2015. Depending on the report you look at, between 2% and 4% of all US employed people work in a call center of some kind.

 These are big numbers and that’s a big market.

So why are these numbers important to anyone in the contact center business? 

DATA, DATA, DATA and BIG DATA!

There are people employed in these positions and they’re handling billions of calls a year from consumers.  For those of you in the back row, the call center is likely to be your Company’s single biggest source of information about your customers – and if your company’s executives aren’t aware of this, then as a call center professional, you have an obligation to point this out to them, over and over!

Further, adding to this opportunity is the emergence of myriad other electronic channels available to your customers to choose from such as email, your web page, web chat, social, smartphone/messenger apps, SMS/MMS and now even video.  In fact, in its 2016 Global Contact Center Benchmarking Report, Dimension Data is claiming that these alternative channels will have surpassed voice by the end of 2016.   Regardless, in both direct and indirect ways, your customers are telling you about themselves, what they want and what you should be doing.  They are talking about you to their friends – they’re recommending or dissuading them from doing business with your company…and explaining why!

All this information – the voice of the customer – is accessible for you to mine. 

So the answer to making your call center relevant is in the data.  Easy, right?  Of course not.  In the next installment of this series, we’ll discuss why there is no easy button.  We’ll explore the challenges and by understanding them, we can arrive at our answer and provide the tools for building a case for making your call center relevant.