We were recently asked:
Given the number of different contact channels we have today, how do you compare productivity across voice, messaging, email etc. i.e. How do you establish if one is more productive than the other?
We put this question to our readers, and have collated their responses below:
Each Channel Has a Different AHT
Historically speaking, each channel has a different AHT.
To compare productivity on each channel, you could:
- make sure you compare apples with apples, meaning you have to find a common comparable denominator between channels. Also, you have to be comfortable with the fact that there is no concrete way of doing it, so there is some error margin involved; but as long as you run the same calculation, results can be compared reliably
- decide on the metric to use for all channels (AHT, IPH) and define how you calculate it
- use historical data to set the right KPI for each channel
- drive performance/improvement by channel-specific actions and compare the outcomes; this way you level different channels to the common denominator (achievement to historical set KPI)
e.g. – voice channel – historical average 300 AHT improved to 275 AHT = 109% achievement vs. email channel – historical average 10 cases per hour improved to 12 = 120% achievement => in this example the email channel is more productive than the voice one (as the email channel delivers more compared to the historical expectation).
* Please note that this is only addressing the productivity subject and assumes the quality levels remain constant.
Thanks to Emil
Split Into Teams and Create a Benchmark
A few years back I encountered the same instances, as we also manage both the voice and non-voice processes.
So, what I did was I split off 2 teams: Team A and B, and split the task by the channels.
Then, I swapped the process between the teams to analyse the AHT info.
There might be some other way to identify productivity, but I found this was effective to create a benchmark.
Thanks to Krishanu
Use a Fortnightly Scorecard
A multichannel contact centre presents a new challenge, hence it can be overcome by using other tools – Fortnightly Scorecard with fortnightly incentive / reward & recognition.
This scorecard has key metrics such as KPIs – Adherence, Quality Audit of interactions in all channels, NPS / CSAT and Wrap % (time spent by agents in After-Call Work).
The scorecard has targets, qualifiers and zero reward for agents with critical errors.
The above metrics look after both productivity and customer experience.
Further, I rotate multichannel roles across the teams so that every agent gets an opportunity to work on calls, chat and email – strengthening the concept of a multiskilled workforce.
The rewards from this concept – Fortnightly Scorecard – have far exceeded our expectations, and we review KPIs every six months responding to business requirements and incorporating employee feedback.
Thanks to Raj
Measure Customer Satisfaction and Quality Score
I think the best measure is customer satisfaction and quality score.
Consider using templates for both chat and email while recognizing we don’t live in an all-template world and some will require the ability to draft free-form and/or variables.
Depending on the level of automation, those could take longer. Some enquiries will require more account research than others.
I know all of this results in an overall average handle time of some easy enquiries with some more difficult questions, but you will need to know how to identify the difference between those types. Create enquiry types similar to call wraps.
Thanks to Bonnie
Look at First Contact Resolution
I’m surprised that no one mentioned looking at first contact resolution as part of this process. It’s easy to churn through interactions, which might give the illusion of high productivity, but if you aren’t quickly and effectively resolving, it’s moot.
I had the opportunity once to consult on a programme. They were doing very well in non-voice channels, chat and email. However, it was requiring 3-4 agent email replies to close a case, and while chat performance was stellar, a huge portion of the contacts were simply redirecting customers to voice: “Sorry, but you need to call for this issue.”
Looking at this in the context of the entire customer journey – contact to resolution – the story would be very different. KPIs were great, performance was sub-optimal.
We needed to change training and process for chat agents, to allow them to resolve more of these contacts in-channel. Chat performance ‘fell’ when looking at handle-time metrics, but the reality was that overall productivity improved dramatically.
Optimizing email required modifying the contact forms to collect relevant information up front. Handle time went up, but volume fell as fewer replies were needed.
Don’t let the KPIs distract you from the bigger picture.
Thanks to James
Look Beyond Productivity
If we’re looking solely from a productivity standpoint, then it’d simply be a case of number of interactions handled / productive time on that channel. However, there are several other factors to consider:
How do customers feel about their journey?
NPS/CSAT data tells you a lot and some channels may be more suited to certain target markets. Customer retention is as vital for businesses as new customers, otherwise you have potential untold loss which is difficult to measure.
Additionally, what are advisors working?
Are they working on one specific channel at a time or are they perhaps taking a mix of channels using one platform? (Some channels evidently shouldn’t be mixed, telephony and chat for example.)
You may even want to take employee satisfaction into account.
It is usually more difficult to hire telephony operators than for other channels as there’s a general hesitancy towards telephony as a channel. Employees that are less happy / not engaged with the business may not be as productive as others.
The initial interactions handled / productive time will give a generic sense of which channels are more productive; however, there are ways of maximizing each channel through the above.
Thanks to Joshua
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