March 20, 2024

Answer Contacts, Solve Problems: Making life easier for Experience & Support Executives

The article discusses the challenges faced by businesses in providing effective customer service beyond basic inquiries, emphasizing the importance of availability across different communication channels and the need for precise forecasting of contact demand to enhance customer experiences

Answer Contacts, Solve Problems: Making life easier for Experience & Support Executives

New mobile apps to keep an eye on

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What new social media mobile apps are available in 2022?

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Use new social media apps as marketing funnels

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Try out Twitter Spaces or Clubhouse on iPhone

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Try out Twitter Spaces or Clubhouse on iPhone

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This seems to be the basics right, we all expect this when it comes to service and support- answer my contact and solve my problem! Keep it simple.. but what is happening today, is just insane when it comes to anything outside of basic service issues. Think of this as your – WISMO calls, Balance, Payment, Rebook Flight, Modify Stay, all the basics we typically see minimal friction. When it comes to, I am using your product and I just imported 10K plus records that didn’t merge, or its your 3rd call due to a fraud issue, or hey insert any issue outside of a “basic” service journey – where you just absolutely just wanna ... REACH OUT AND TOUCH SOME ONE!!! :)

To answer the call well... you need to be available. Be available – Lets think about this.... We have companies who can answer the phone in 30 seconds or less... then, we have companies who take anywhere between 5 minutes – and ... to infinity and beyond. Now – the true dilemma in this case is more so related to the process by which service is viewed.

Here’s a little hard truth. For many businesses, there is a concentrated effort to migrate customers to what they call cost effective channels (Chat) period, they mean chat. They do so with the hopes of concurrency and being able to effectively handle demand. To date – there is no productivity insight into the actual concurrency rate which is hyper-published; go look at the Salesforce Dev community, go look on blog boards and code hubs, I have yet to see an agent say, yes – I can see my concurrency rate day over day. Lets hit-cha with some more – and get this.... they can’t even see a metric we created .. AOPAc ( Average offered per accepted chat) this is the number of chats returned to queue which were presented to an agent but did not get picked up.

We know there is not data consumed around this because when it comes to actually forecasting this data – no WFM tool accounts for productivity accurately. Which is why depending on contact demand, and the disparity of data, you could be talking to an agent whos' average response time per session is 3-5 minutes per each customer response; and for some issue types, this is an extremely painful channel – plus guys... typing my problems – seriously – you want me to type my problems over and over on a channel with no means of accessing any other channel? That’s right – for some businesses the voice channel is so prohibitive it is non-existent within the service model.

Forcing channels on customers prescriptively vs. understanding issue and customer preferences really creates a multitude of problems, including repeat contact demand, re-work, poor CSAT, and ultimately churn. Its still baffling to me that accessing the voice channel for customers is still harder than ever. Businesses instill IVRs to help route contact demand and in the process deemed it necessary to utilize Ai to pick up me breathing and saying “I didn’t understand you” , or god forbid a car or loud noise comes into the picture, yep – again “I didn’t understand you, great googa-mooga.  

While we have systems which are needed to provide essential capabilities within the contact center environment; we are still not doing the basics right when it comes to being “Available”. The right channel for an operation may not be the best channel for customers, and the issue types which exist, could be deemed too difficult by customers for the channel provided.

Just because you staff a channel up for availability, it is not necessarily delivering on the promise of concurrency and AOPAc as we see across industry – many customers are not measuring cost per contact, instead they are modeling cost per case – eroding the true net productivity/efficiency view of contact centers.  

When it comes to being available, customers really don’t care if you want to prioritize a channel. Even with poor wait times, customers are still willing to wait to get a human interaction over the phone to solve their issues. Of course we have tools to help us be available ... even with WFM tools today, we still get subpar forecasting capabilities from these technologies. I said it ... yes indeed... for a simple reason.

Today, the evidence of this is seen when we look at how each of these tools views contacts, interactions, chats, emails... all of these are viewed as the same type of unit; and what we know to be true is repeat contacts, that’s to say – contacts 1,2,3,4 etc... each have a longer AHT than there predecessor and each of those are connected from the experiential lens not the operational lens. Dramatic pause.... Think about that!

We have been forecasting contacts like they are all the same thing.... not unique , not different, and therefore – every forecast – has been wrong since the inception of Erlang-C being utilized to predict traffic. Businesses need more precision when it comes to forecasting contact demand, and not only for voice, but for all channels. Even with the modern technology that exists the ability to truly forecast contact demand down to the 15-minute interval, well its just not done, most stop at the hourly level and thus businesses fail to meet customer demand.

With major peaks and valleys throughout the intraday and less precision, businesses end up staffing to lower levels, prioritizing cost containment without realizing the net impact of repeat contact demand. The other channels like chat, end up not factoring true net productivity as I mentioned above; and this just creates subpar channel performance.. and ... get this at the true cost per contact level when we come into a majority of operations, we find there chat and phone calls at nearly the exact same "Cost Per" ... ouch!

serviceMob provides an experiential forecast to help businesses transform the view of the data so businesses have a better representation of customer effort in their forecasts, bringing unparalleled precision at the IWP (Intraweek Pattern) level with +/- 3% accuracy. Being available may seem like a commodity in todays contact centers, the truth is harder for so many businesses today, who simply cannot get the right forecast into their WFM tools.

This makes being available even harder with teams using what we in the industry call “Peanut-Butter” to smooth out the peaks so they have a little more headcount to avoid being out of SLA during higher traffic periods. This is also known as the “Art” side of the WFM. By removing the barriers of dark data as the exist today, this provides serviceMob the ability to help businesses enhance the way businesses stay “Available”, and be ready to --> Answer the Call!

In the context of service we need to make sure teams have the right data model to get the best forecast based on the experiences your customers have vs. the operational efficiency lens by which we look at a forecast and staffing.

Next up, lets take a look at how we quantify the customer experience. The data we use – and that largely goes unused in service beyond operations – is focused on Efficiency, Quality, Productivity, and Operations. The tough question for executives to answer is “How many customer experiences did we have, what is the nature and behavior of those experiences, what channels are those experiences happening on, what agents are struggling to solve specific experiences as it pertains to support and service.

There are a host of other questions we can / should ask as it pertains to the experience from there – but all of this is not accessible with the current technology, BI tools, and data science teams tackling this – it just doesn’t exist... full stop. The truth is, no one really has this .... its all fractional; everyone wants the full story but instead there all reading chapters out of sequence with no connection to what happened previously ... Too much hype has been promoted over data which lies in the area of cases/tickets.

This data while operationally useful, and again – extremely essential for the operation, we know this to be true, its just ... the data is not extended to the teams causing support contacts. In the world of “Resolution” there are two types of resolution which the business is responsible for, the first is “Service Resolution”. This is where we as an “Operation”, we have an opportunity to prevent the re-work or repeat contacts into the business. This responsibility is typically with management teams which are focused on agent level effectiveness at solving specific issue types and prioritizing those issue types for coaching / training / KM articles etc.

The second type of resolution type the business must prioritize and often cannot; is “Issue” Resolution. Issue resolution is not, I repeat – IS NOT – the responsibility of the service operation, it instead is a responsibility of the business units which caused the contact demand to begin with. Here are a few examples: In SaaS think of this as product/engineering/success/marketing, in the context of retail this could Marketing/Marketing Ops/Fulfillment/Sourcing/Procurement, in Hospitality this could be the Property Teams/ Booking Teams/Housekeeping/Front of House, etc. All of the business units across any industry which cause contact demand often find it difficult to consume and “Prevent” contacts, or improve their processes as such which they at least reduce the level of effort exerted to solve the issues created.

The data of service is too often consumed internally and does not have extensibility to help the enterprise as a whole to protect both the top and bottom line – Service; is too often validated as qualitative and a cost center vs. a revenue protection center quantifying the experiences customers have with their service/support.

At serviceMob we are helping businesses actually improve the customer experience by quantifying experiences to reduce contact demand, but also as noted we have improved the forecasting process by deploying a world class model to experientially forecast with precision. We know there are plenty of essential tools in the Franken-Stack of service, but when it comes to real world customer insights – there is only one unified intelligence provider, and for those familiar with "The Highlander" – there can only be ONE... serviceMob sits on top of all the technology within the Franken-Stack Tech-Scape of service, so you can actually see-measure-action-resolve-and transform your customer experiences!

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