A Funny Thing Happened on the Way to Your Inbox

We’ve all experienced that heart-in-your-throat moment:  “Wait.  Did I hit Reply or Reply to All?

nervous on computerYou cautiously check your sent messages.  You want to look, you are afraid to look… you have to look.

Or even worse.

You don’t realize your mistake until the responses start pouring in.

reply to all cartoon

You may remember the student from NYU that meant to forward an email from the bursar’s office to his mother, but instead hit ‘reply to all.’  An event that became known as Reply-Allpocalyse.  This one was tame, the students joined in and had a good time with it; the only victim was NYU’s email server.

Then there was this poor guy.  His boss sent out a company wide email giving directives on a new project.  He meant to forward the email to a coworker in which he added honest assessments of their colleagues, and how valuable they would be on the project – but he hit ‘reply all’.  Everyone in the company received the email, including the colleagues he was speaking about.

We recently had an email mix-up at work.  While it was no ‘Reply-Allpocalyse,’ we all got a chuckle about it.  The main characters are Chris (a Telovite), Maja (who wasn’t supposed to get the email) and Christian (who was).  Here’s the story:

We had a couple of busy weeks recently, between Thanksgiving Holiday call traffic, vacation time and illnesses. This lead to a very hectic communications exchange and at some point some wires got crossed. Chris went to his inbox to respond to a recent email from Christian.  Instead of opening Christian’s email, he inadvertently opened an email from Maja.  He began to address Christian’s issue.

At the last second Chris realized he was supposed to send the information to Christian and his name was not in the To or CC field. He quickly added Christian’s name without any thought to Maja’s email address being in the To field.

The email was sent – and here’s what happened:

Maja:  I am curious, why did you CC Christian?

Chris:  I’m sorry, Maja. Please ignore my previous email. That one was not intended for you and was on a completely separate subject for another client.

Christian:  Just an FYI, you sent this to another client as yours as well. Not sure if this was meant for her, for me, or both.

Chris:  Thank you, Christian. I was working Maja’s issue around the same time and started back up with the wrong draft. I’ve emailed her an apology. Thanks for catching my mistake.

Christian:  It’s ok, I actually know her from a past job so if anything that was a fortuitous mistake as we are now catching up.

And Maja also wrote me back:

Maja:  I only ask because I worked with Christian 12 years ago and last week I wanted to look him up on LinkedIn. When I saw his name, I thought to myself, I wonder if this is the same Christian? And then I got below email……life is crazy sometimes.

Christian included this in one of his replies:

From Christian to Maja:  Not sure why Chris sent this to both of us, but your name rang a bell and after a quick look-up I realized I did in fact know you. Way back around 2000, I was consulting at Student Resources I think it was called, and we worked together for about a year. I want to say Diana was our coordinator.

Anyway, glad to see your doing well. I enjoyed our time there together, not so much the work but the conversations. I still go to all the good Croatian bakeries you told me about. And in fact I have been to Croatia several times since then, along with Slovenia, Montenegro and Serbia.

They continued an email exchange, catching up as old friends.

Maja is right – life is crazy sometimes.  It’s the unexpected moments, like reconnecting with an old friends, that make it so sweet.

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Product Spotlight: VocalQ

Product Spotlight:  VocalQ

How many times has a customer service experience left you feeling like this:

Maybe your experience was so poor, you decided to take your business elsewhere.

Now imagine you are the business owner.

Customers are leaving and their chief complaint is customer service.  Right now your business measures quantitative call data:  how many calls are received, how many are abandoned, how many rings before a call is answered, length of call, etc.

You review that data and it doesn’t tell you much.  You can tell if customer calls are being answered right away, or if customers are hanging up before they get through to a live body.  It also tells you if you customer service reps are spending enough time on the call to reasonably answer questions and provide support.

What you can’t tell from that data is the quality of the conversation.  Are your reps rude to your customers?  Are they able to answer the caller’s question, or is more training needed?  Is it all your reps, or just one?

Enter VocalQ.

You are familiar with the measure of your IQ or your EQ (emotional quotient); VocalQ (VQ) is your vocal quotient.  It is the measure of your communications intelligence within your business.

VocalQ, tracks your quantitative and descriptive data, but it provides a deeper analysis of calls made to your business.  It records conversations and will alert you on the quality of the interactions between your employees and your customers.

Calls are sampled and benchmarked.  Things like the customer having to repeat themselves or reps providing the correct answer to questions can be measured.  You can also identify words or phrases that will trigger a message to you.

If you want to know every time a customer says: “I am not happy” or mentions a competitor, you will be alerted.  When a customer hangs up, unhappy, after a customer support call, you run the risk of losing that customer to a competitor.  You also lose potential customers as well.  An unhappy customer will not recommend your business to family and friends.

So, you’ve been notified that a customer called in and said “I am not happy with my service.”  Now what?

You can be the hero that saves both your days.

You can swoop in and give the customer a call and say: “I understand you called in for support – I just wanted to ensure that your problem was resolved.”  Knowing that it wasn’t, you will be given the opportunity to make it right.  You now have a happy customer.  And a happy customer doesn’t look for other options.

Click here to learn more and discover your VocalQ!

Making Sense of Telecom Jargon: Audio Mining

What is Audio Mining?

Have you ever used the app Shazam?  If not, it’s great.  A song comes on the radio, you think “wow!  I want to download this song…I wonder who sings it?”  You wait to hear the DJ announce it, and you are in the middle of an hour-long, commercial-free set.  You’ll never know.  But, if you have the Shazam app, you just open the app, hit ‘tap to Shazam,’ quietly stand-by while your smart phone listens and within seconds, you are provided with the name of the song and the artist.

That is musical audio mining.  Shazam identifies the melodic, harmonic or rhythmic characteristics of the musical piece it’s listening to, and then searches its database for the song that bears the same characteristics.

Or…

How many times have you called in for customer service and/or support, and have been told: “this call may be monitored or recorded for quality assurance”?  Too many to count, right?

That is also audio mining.

Audio mining is the process of searching large volumes of recorded audio for occurrences of specific words and/or phrases.

There are 3 ways a program can analyze a conversation:  Large Vocabulary Continuous Speech Recognition (LVCSR), Phonetic Recognition, and Hybrids programs.

Large Vocabulary Continuous Speech Recognition (LVCSR)

LVCSR relies on a database, or dictionary if you will, of words.  It uses this database to understand what is being said during a call.  You can enhance your LVCSR database with industry-specific terminology or words or phrases that are unique to your organization.  You can also add new terms and phrases to your database as needed.

For example, imagine you are a company that specializes in specialty dog treats and you are considering adding an organic line, but you are not sure if your customer base is interested in this type of product.  You just add “organic” to your database, pick a time period to analyze (say, the last year) and then reprocess the recorded calls during that time period.  You will be given a report that lets you know how many times, during the given time frame, customers called in and the word “organic” came up in conversation.

Phonetic Recognition

A system that relies on phonetic recognition does not search for words or phrases, nor does it make any attempt to try and understand the meat of the conversation.  This system strictly searches for sounds that make up words and language.

It is quicker than LVCSR, but it has a higher degree of inaccuracy.  This system cannot differentiate the different meanings of the word stock.  It also cannot recognize the difference between buy, bye and by.  So imagine you want to do a search for calls in which your customers say: “buy.”   You will have to sort through conversations in which a customer says “bye” or “by” as well.  You could waste a lot of time listening to calls that won’t provide you with the insight you were hoping to gain.

Hybrid Solutions

Hybrid solutions rely on the best of both of these worlds.  They combine a large database of words with phonetic analysis.  The result is faster, more reliable search results with better comprehension of the conversation.  This system can analyze calls made to your business and organize them into the categories you chose:  customer complaint, billing, products…you name it!

Imagine, you receive a report and there has been a spike in calls containing the following words/phrases:  “I need to speak to a manager,” “unresolved,” “same problem.”  You can feel fairly certain that your customers are having issues that customer service is unable to resolve.  You can then take the steps to determine if someone in customer services is not doing their job, if your customer service reps need more training to assist customers, or maybe there is an issue with your product that needs to be addressed.  In any case, you will be able to contain this issue before it spirals out of control.

Prior to audio mining solutions, businesses may not have been made aware of problems, until they started losing customers.  By then, it’s too late.

To learn how audio mining can help your business, please click here.

4 Key Benefits of the New VocalQ℠

Used effectively, the VocalQ framework is a strategic differentiator and delivers considerable benefits.  Speech recognition and analysis has come along way in the last decade and the technology is poised to accelerate in the next.  The day is not too far off when speech recognition and analytics will morph from improving customer interactions to being the customer interaction.  Our goal with VocalQis to help companies realize the benefits:

Reduced Costs  – Companies gain valuable insight into the inefficiencies of their operations.  Speech analytics help to decrease call times by training agents to be more effective in harvesting information from customers.  Currently, many businesses measure quantitative call data like; how many calls were received, how many calls were abandoned, how many rings it takes to answer an inbound call, etc. This data only answers “what” communication is happening within your business. VocalQ measures the context and content of your communications.

Better Customer Retention – Cash spent on retaining customers through improving customer service is far less than that needed to gain a new customer.  In addition to measuring quantitative and descriptive data, VocalQ goes a step further by recording and alerting on the quality of interactions. With VocalQ, What's Your VocalQ?calls are sampled with call recording and the dialog is benchmarked.  Things like customers having to repeat themselves and correct responses to questions can be measured.  Furthermore, the recorded conversations can be compared against customer surveys so supervisors can discover why an interaction went well or went awry.

Cross Selling – Speech Analytics identify opportunities to increase sales conversion rates, both for new customers and up-sell and cross-sell opportunities.

Reduced Risks – Using speech analytics enables a business to quickly identify potential regulatory failures or locate poorly performing agents.  Rather than relying on gut feeling, you “hear” the voice of the customer, analyze the interaction in real-time, and make better strategic decisions about your company.  The ability to take immediate action on “voice alerts” is another benefit of VocalQ.  Supervisors can identify critical words and phrases in conversations and receive real-time alerts to remedy the situation now rather than later.

What other benefits have you experienced with the New VocalQ?

A New Framework for Evaluating Customer Interactions

Today we propose a new framework for analyzing and improving customer interactions within your organization.  Rather than rely on quantitative and descriptive measurements, such as rings to answer, we suggest shifting the focus to the quality of interaction and prescriptive measurements.  In this framework, calls are sampled with call recording, and the dialog is benchmarked.  Things like: customers having to repeat themselves, and correct responses to questions, can be measured.

What is Your #VocalQ?

Recorded conversations can be compared against customer surveys so supervisors can discover why an interaction went well or went awry.  Supervisors can listen for a tone that is professional and empathetic.  A qualitative score is determined and the best conversations then saved for future customer service training.   This framework for measuring customer interactions – both in a descriptive and prescriptive manner – is outlined below:

Measurement Criteria

Quantitative

Qualitative

Prescriptive Measuring metrics that directly effect customer satisfaction and taking action on them.

Example:  Average wait times exceeding prescribed limit

Action: Automatically put more agents in the queue

Monitoring actual conversations in the customer engagement and using voice triggers

Example: Recognizing words that indicate positive experience and saving conversation

Action: Measuring other agents against the positive interaction

Descriptive Data that describes the details about the call

Example: Call Detail Logs (answer time, time of call, duration, etc.)

Data or recordings that describe the details about customer conversations

Example: Measuring how long it took the customer to get their issue resolved.

An example of using this framework:

Record the first request of customers, and then capture the response of the service representative.  The reaction of a representative to a hostile customer is often key to defusing a tough situation.  Phrases like “I am sorry a mistake was made” versus “I am sorry I made a mistake” can steer the conversation in a different direction.   The context is what is important and prescriptive/qualitative data about what was said helps improve the engagement.

The ability to take immediate action on words that we call “voice triggers” is another benefit of this framework:

Supervisors can identify critical words and phrases in conversations.  Phrases such as “system outage” or “I am down” are used to trigger text messages to supervisors who can automatically add customer service agents into the queue.  The ability to address problems immediately improves the processes and procedures at the frontline that drive the business.

What is your Vocal Q?