- [Morgeson] Okay, welcome to ACSI Analytics.
This is the new customer experience management tools
from the American Customer Satisfaction Index,
available exclusively
through Microsoft's Customer Voice platform,
the Dynamics 365 Customers.
I'd like to very briefly walk you through this new platform
and show you how it can help you better understand
and better manage your customer experiences.
The ACSI Analytics tools
are based on a statistical impact analysis machine.
Basically, these powerful tools allow companies
to obtain real time outputs to identify what customers like,
what they don't like and where to focus improvements
that have the greatest impact on customer satisfaction,
retention and financial performance.
Once the Dynamics 365 customer
chooses to complete their project
through Customer Voice platform using ACSI Analytics,
we begin our process.
And as you see here
what the Customer Voice and ACSI Analytics interface
allows the user to do
is access a database of rigorously tested
and widely adopted survey items.
And you see some of the examples
of those kinds of survey items down here.
Available within the survey items
that you're able to use within the Customer Voice platform
are included the satisfaction metrics from ACSI.
These will allow you to benchmark with ACSI data
and ACSI scores
for many large companies across the US economy.
We've also as you see here got additional metrics
and these kinds of metrics
this is all examples from the banking industry,
will allow you to tap more closely
into the kinds of experiences your unique customers have
and how they are feeling about their journey
through your business as customers.
Once you've collected your data
through the Customer Voice platform in ACSI Analytics here,
you see that you can add your individual survey items
to a series of different metrics.
And essentially what these metrics do
is allow you to take multiple survey items
and include them into individual constructs,
what we call latent variables.
Essentially, these are a way to more accurately and reliably
measure parts of the customer experience,
including customer satisfaction
with the ACSI customer satisfaction questions,
but additional metrics that you see down here as well.
And we have an example here of branches and ATMs.
These are from the banking industry,
this particular example.
These branches and ATMs will allow you to measure
for instance survey questions
that ask about the number and locations of branches
and the number of locations and the locations of ATMs.
Those kinds of items can be put together
into single latent variables that more accurately measure
portions of the customer experience.
Once you've collected your data
and created these constructs that I'm talking about,
and we'll go ahead and save those,
this is where the ACSI Analytics tool
really becomes most useful.
Here you'll see that you're able
to look at scores from the various variables
that you've collected on these metrics.
We see a predicted ACSI score here,
this is your customer satisfaction score.
And we see a comparative benchmark down here at the bottom.
We also see some outcomes of customer satisfaction,
like customer retention.
This is an estimate of customer retention you see here,
but maybe most importantly we've got over here,
a customer asset value estimate for this company.
And this essentially tells you the value of your customers,
their profitability over their lifetime,
given current levels of performance on the CX metrics,
customer satisfaction, and customer retention.
But of course, just looking at this data,
benchmarking and comparing these scores isn't enough.
What we wanna be able to do is
through this prediction simulator
which is powered by Power BI and Microsoft,
is to go in here and look at what will happen
if we make improvements and changes to these scores.
And so we've got three examples here
of scores for the banking experience,
branches and ATMs, financial products, and mobile app
and we'll go ahead and assume that we've made improvements
of five points to each of those.
Here we see the improvement to customer satisfaction
that the model predicts,
as well as the improvement in customer retention.
And most importantly down here
we can see the gains plus 22%,
and the estimated asset value of our customers
based on those improvements
in the CX metrics, satisfaction and retention.
And it's really this feature
in the ACSI Analytics prediction model simulator
that allows companies to best understand
what will happen to the value of their customer assets
by improvements to their customer experience.