Episode Transcript
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Ian (00:07):
If one word could sum up
the modern utility-customer
relationship, I thinkcollaboration and engagement
might be tied for first place.
Adoption of newer technologieslike electric vehicle charging
equipment, connected devices,and solar plus storage systems
give customers greater insightand control of their energy
consumption patterns, andthey're demanding better service
(00:28):
from their utilities.
Still, it's interesting thatmany customers remain passive.
They're unaware of programs andresources available to them,
and utilities aren't alwayseffective in reaching customers
that should be prime candidatesfor their programs.
And as energy costs rise acrossthe US, proactive customer
engagement and education is moreimportant than it's ever been.
(00:50):
Hello and welcome to the EnergyBeep Podcast.
I'm your host, Ian Perderer.
And today we are joined by AlexCorneglio, Vice President of
Product Management at Brilliant,and he's here to discuss the
importance of precise andproactive utility customer
outreach and the role that dataplays in those communications.
Today we're going to answerquestions like how can utilities
(01:11):
take advantage of data tobetter segment, target, and
communicate with customers?
And how do more effectivecustomer connections benefit
both the customer and utility?
So with that, let's getstarted.
Welcome to the show, Alex.
Tell us a little bit about yourbackground, your current job,
and what role your employerBrilliant plays in today's
(01:33):
energy market.
Alex (01:34):
Absolutely.
First off, thanks for havingme, Ian.
Excited to be here and excitedto talk about this stuff because
it's a topic that I've devotedprobably the last decade of my
life to.
So I've got a lot to say.
Hopefully it's helpful.
And let's let's jump into it.
My background is engineering.
I'm an engineer at heart, andright out of university, I
started working in energy andjust got hooked.
(01:56):
So my journey in the broaderenergy space has lasted for, at
this point, 20 years.
Hard to say that.
And I've done everything fromoil field services to solar and
now very much focused on utilitysoftware, particularly for
about the last decade.
I'm the co-founder of Energy XSolutions, and we started that
(02:17):
company about 10 years ago toreally try to solve the problem
of utility customer education.
Our vision was that we saw thaton-site building energy
assessments were really the bestway to characterize energy
potential and give customers theinformation that they needed to
ultimately take action.
And we really wanted to scalethat.
(02:38):
We wanted to scale energyassessments through technology.
And then Energy X was acquiredby Brilliant.
And now, as you mentioned, I'mthe vice president of product
management.
And my job here is to takethose same sort of ideas that I
was working on before and reallyexpand them.
And now instead of just beingfocused on customer education,
(03:01):
we have access and purchaseacross the entire customer
journey.
So we can take customers allthe way from engagement through
fulfillment, and we can do thatfor almost any utility program
and offer.
So I think where my focus isand what Brilliant is really
trying to do is to take some ofthe solutions that historically
(03:22):
maybe were really pointsolutions.
They were focused on certaintypes of programs or certain
types of initiatives and reallygive utilities and governments
and efficiency organizations theopportunity to apply that
technology across their entirecustomer journey.
Because I think, as youmentioned in the intro, we are
really looking at a much moreholistic energy landscape today,
now more than ever.
Ian (03:43):
Yep.
So you mentioned the customerjourney and let's set the stage
a little bit for ourconversation.
I like to think of utilities asunique in some ways in the
marketing sense.
And yet at the same time, theystill have to adhere to a lot of
the same rules and constraintsand realities everyone else is
(04:03):
dealing with.
But I think the utilities spaceand its journey with customer
engagement is a bit of aninteresting one that would
probably leave most marketers inthe for-profit or tech sector
scratching their heads a littlebit.
So can you describe the oldstyle of customer engagement we
used to see in the energy spaceand then catch us up to like the
(04:25):
now?
So maybe that last three tofive year interval, how does how
does that old style contrastwith what we're seeing today in
the utility space?
Alex (04:34):
That's it's a really
interesting question.
And I think what I'm what I'mcoming to the conclusion of is
that in in some ways, you know,things have changed completely.
But in other ways, it it'sstill the it's still the same
game.
And what we have today aremaybe better tools, maybe a
deeper understanding of the ofthe impact that we create and
the outcomes therefore thatwe're able to drive and achieve.
(04:58):
But I I think in a way, andmaybe you'll see this too, you
know, the the story is the same.
And if we go back way back, Imean, it's always been about
mass marketing.
If you go back, you know, 10years, 20 years, utilities have
been tasked forever with thechallenge of effectively serving
everybody.
And that's a complicated order,no matter what tools you have
(05:21):
at your disposal.
So I think if we go way back,the strategy of the utility was
that they had a couple of thingsthat they really wanted to talk
about with their customersbeyond just the please pay your
bill and there's an outage andthe the regular transactional
communications.
And the idea behind massmarketing is that you you push a
message out to everyone and youtry to get that one to two
(05:41):
percent conversion rate.
And I think what we've reallyseen over the last, in
particular, maybe it's happeninga little bit before this, but
now in the last three to fiveyears, I would say this has
almost become table stakesacross most of the utilities
that we work with at Brilliant.
It's it's the rise of moderndigital customer infrastructure.
(06:01):
So almost all utilities nowhave a customer information
system or a CRM in place.
They're all utilizing cloudinfrastructure.
AMI data is available, it'sproperly warehoused, it's being
properly processed, and it'salmost expected that that
information is going to be usedin a variety of customer
engagement strategies.
Other tools as well, that maybe10 years ago people were saying
(06:24):
that this is going to be thefuture.
Well, now it's here.
You know, everyone or manycustomers are paying their bills
online.
Almost all utilities havecustomer portals, they have
billing offerings that rangefrom budget billing to flat
billing to a fairly at leastrobust understanding of what
income-qualified customers mayneed from their utility.
There's lots of ways to pay,there's different rate options.
(06:46):
And I think that we're also nowseeing that messages are
turning more into notifications,if you will.
Like we're already using thatwealth of information and those
technology tools to be moreproactive with customers,
letting them know in the middleof the month if we think the
bill is going to be high at theend of the month.
These are normal things,allowing people to interact with
(07:06):
their utility across a wholebunch of different media.
Calling them up is definitely ahigh cost channel, but it's
certainly no longer the onlychannel for people to get in
touch with their utility.
And so I think that what'sreally come about is that we've
gone from this era where we wereusing just the basic
information to be able tocommunicate with sort of
(07:27):
everyone all at once.
And now we have a plethora ofadditional information about our
customers stored in new toolsthat are able to really drive
proactive service management.
And I and I think that'sexciting.
Ian (07:41):
I 100% agree with that.
You know, you've been in thecustomer journey marketplace for
energy for about 20 years.
I've been in clean energymarketing for about a decade
now.
And, you know, in some ways,marketing and customer
engagement, it's not unique inenergy, in the sense that data
is going to make or break yourefforts.
(08:02):
But I think what is unique isthe kind of data I think
nowadays that is really trulyvaluable isn't something you can
find in your Google Analyticsor your Instagram dashboards.
You know, it's it's harder toaccess.
And it's something that youhave to take care to set up.
For example, I know one of thethings that you're doing at
Brilliant as you look atproperty data to better
(08:24):
understand and target customers.
So let's take property data asan example.
How does that help utilitieshone in on the right customers
better than the data that theyare traditionally collecting?
Alex (08:36):
Right.
Property data is our way ofgoing beyond the bill, if you
will.
To summarize, sort of my lastanswer, the the customer
engagement game in the utilityspace has always been, to a
certain extent, about massmarketing.
And what we've realizedrecently is sort of full
(08:59):
utilization of all of the dataand technology tools that the
utility inherently has at theirdisposal.
And so if we're gonna ask thequestion of how do we go, how do
we go further, how do we drivebetter results on top of that, I
think, or at least Brilliant'sanswer is that we've got to
bring in additional context.
We've got to be able to alsounderstand what's happening, as
(09:21):
I mentioned, beyond the bill oror outside of that utility
customer relationship.
And if you think about it,property data makes perfect
sense.
So we're talking about, youknow, information about the
building that has the meterattached to it.
This is what's driving thebill, this is what's driving the
consumption.
And if we can understand thebuilding and the consumption,
(09:42):
then we have a much betterpicture, not only to proactively
suggest things to customersbecause we know what their
building needs, not just whatwould benefit their usage, but
we can also start to betterunpack the impact that we're
generating.
We can start to sort throughall of the noise that comes with
(10:04):
consumption data.
There's estimated billing,there's occupancy changes,
there's weather, there's marketfactors, macroeconomic factors,
rate changes.
All of these things areencapsulated in the data feed
that you get from a bill.
And it's just great to havedata about what the energy is
actually being used for, i.e.,the building, the property, to
(10:25):
be able to put that in deepercontext and make more targeted
usage-independentrecommendations.
Ian (10:33):
So when we say property
data, what are what are we
really talking about?
I mean, is it beyond and moregranular than maybe what you
would get in an MLS listing?
So things like the year thehouse was built, how many
bedrooms it has, or is it evenmore granular to the point of
like, okay, well, based on ahouse this size, it probably has
(10:54):
a water heater of like thiscapacity, which draws this much
kilowatt hours andda-da-da-da-da-da-da-da.
Alex (11:00):
All of the above.
All of the above.
And so this is kind of wherewhere we go back to this idea
that, you know, if you want to,if you really want to understand
a building and how it operates,what do you do?
You get an expert to come inand do a 200-point audit and run
all of those data pointsthrough building modeling
software, and you can reallystart to calculate and
(11:21):
understand the usage of thebuilding.
And so we we really want to dothe same thing.
We start at sort of the mostfundamental, which is basically
geographically, where is thisbuilding located?
And believe it or not, thereare patterns that exist between
buildings that are located in asimilar area.
We see those buildings,regardless of their makeup,
performing similarly in certainways, and and that's really
(11:44):
helpful.
On top of that, we then startto layer things about the
structure.
So when was it built?
What's its vintage?
How large is it?
What's the what's the housetype?
Is this a town home?
Is it a is it a single detachedbuilding?
Is it a pre-manufactured home?
Then we start to layer ininformation about the the
equipment, the major pieces ofequipment that are inside that
building.
What sort of heating fuels doesit use?
(12:05):
Does it have multiple heatingsystems?
Once you start to get a moreholistic picture of, you know,
where the building is, what itsmain structure is, what are the
main pieces of equipment, thenwe start to model all the
various ways in which thosefactors, if you will, could
could operate together.
So we're looking at, you know,if this building replaced their
current heating system with ahigh-efficiency heat pump, how
(12:28):
would that change things?
How would that change heat lossthrough the building?
Should we do an insulationupgrade before a heating
upgrade?
Which one would be morebeneficial?
And how do thesecharacteristics relate to other
homes around them?
The last piece then for us isbringing back in that
consumption information andunderstanding, you know, okay,
we understand how the buildingcould operate.
Let's now look at how thebuilding is being operated.
(12:52):
And you can imagine thatbetween those two poles, there's
a whole lot of information.
So we're we're going we'regoing very deep.
We're we're going all the way.
We want to understandeverything that we can about the
building.
We look at a whole bunch ofdifferent publicly available
data sources to get thisinformation.
It goes way below way beyond,you know, real estate data, as
you mentioned, MLS information.
And we're also, you know, likean energy auditor would, we're
(13:15):
trying to model the future stateof the building and include
that in our understanding aswell.
Ian (13:21):
You know, we're talking
about the customer engagement,
but then I think you alsotouched on some other
applications that just havingthat data would have, which
brings me to the next thing Iactually wanted to ask you
about, which is, you know, onceyou have the right data, you
need to put it to its best useand put those insights into
practices.
And at UTIs, the larger theutility, I think the more
difficult that can be.
(13:42):
They are famously siloed, and Iknow there are utilities out
there who are doing some reallyimportant and great work to
flatten out their organizationsand make more integrated teams,
but it's still a work inprogress.
So how can a utility, either ontheir own or through working
with a partner like Brilliant,solve some of these integration
(14:04):
challenges to ensure like whenthey're really getting this
piece of data, it's beingsqueezed for all the juice it
has, so to speak?
Alex (14:13):
Yeah, that's a that's a
really interesting topic because
I think the the answer there,at least from my perspective, is
maybe counterintuitive.
Just because you have a lot ofinformation about a customer,
whatever that may be,consumption information,
property information,demographic information.
It doesn't mean that you haveto use it directly in the
(14:35):
communication, or it doesn'tmean you have to use it directly
in the engagement.
We look at data fundamentallyas just another tool to be able
to understand how currentengagements are going and make
sure that future engagements arebeing optimized in the right
(14:55):
direction.
So let's give an example hereabout how maybe you might find
yourself in a situation at autility where you have to work
across silos and maybe that'llput what I'm talking about in a
little bit better context.
So we had a challenge recentlywhere we were working with the
utility and they had three goalsthat they were trying to drive
with a single communication.
(15:17):
And each of those goalsinvolved a different part of the
utility.
So one of the goals was toincrease customer satisfaction.
Common one, this was driven bya representative from the
communications team.
We also wanted to reduce callcenter activity.
So something was happening,people weren't necessarily
satisfied by it, and what werethey doing?
(15:38):
They were going to the callcenter.
So that then involved the callcenter team, and they were
trying to look for ways tosystemically lower call center
activity.
And then, of course, there wasa program manager involved who
had some efficiency goals, andthey were hoping that these
communications could alsopromote certain programs and
help manage energy usage.
How do you design acommunication that does all of
(16:01):
that, that speaks specificallyto each of those points?
It's really difficult.
What we ended up doing wasfocusing on what we felt was the
core issue.
We started targeting customers,looking at their consumption
information that were havingunusually or particularly high
bills.
And we included messages thatgenerally in past campaigns were
(16:26):
shown to drive positivecustomer satisfaction.
And the hunch was that if weincluded the right type of
information from the bill and weput it in a format that was
already consistently drivingimproved customer satisfaction,
that that would check the box.
So part of the strategy is justlooking at what's worked before
(16:48):
and using that plethora ofinformation to try and provide a
educational experience that'sreally outcome focused, right?
We we took the information fromthe call center, we included
information that would directlyaddress the concerns that people
were calling in with, and weembedded that into a format that
we know is, I don't know, it'sjust a funny word to say, but
(17:08):
it's pleasing to customers.
But then what about theefficiency goals?
Well, the interesting part isthat that's where all of the
rest of the data came in.
We were, after three months ofsending out these
communications, able to use thatbackground data to segment the
campaigns and find customersegments that were actually high
performing in terms of loweringtheir bill.
(17:31):
There was a group of customersthat, if they received three of
these communications in asequence, they would actually
systemically reduce their energyuse by 1.5%.
So all of a sudden, now,because we have all this
background data and becausewe're leveraging communication
methods that we can properlystudy, what we have running in
(17:52):
the background is almost like abehavioral energy program.
So I think like the way thatyou cut across silos is first
you understand the outcomes thateverybody is looking for.
And then you make sure thatthere's sort of a component of
your communication design that'sgoing to address all of that.
But it's not to say that youhave to use all the data.
(18:14):
Certainly, customers were notgetting personalized messages on
the basis of because your homeis like this, we're sending you
this message and we think that'swhat's driving you a high bill
for you.
Instead, we use tried and truemethodologies to drive outcomes
where we could, and we use thedata to help with the analysis
of the third.
Ian (18:33):
So talk to me a little bit
maybe about how this data-driven
targeting, when it's beingapplied in this way, help
utilities increase the impactsof their investments.
I would imagine theapplications are myriad.
Alex (18:47):
Definitely.
You know, at the face value,once we start providing a lot of
this data to utilities, even ifit's not, as I mentioned in the
last example, even if it's notmeant to enhance the
communications or make thecommunications even more
personalized, the first thingthat utilities often get from it
is just a new view of theirservice territory.
(19:07):
It's an opportunity to sort ofscratch your head and say, oh, I
didn't realize that all of theolder buildings that can benefit
from certain improvements orhave certain consumption
profiles all happen to belocated in these specific areas.
And maybe if we just targetedcommunications to those specific
areas, we would see a muchgreater return on investment
(19:30):
from those types ofcommunications.
So there's something to be saidfor just good old-fashioned uh
segmentation and targeting.
But I but I think that thepiece that is often missed, and
that's kind of the punchline ofthe last story as well, where
you know the energy savingscomponent actually came from the
analysis.
We really have to think aboutdesigning communications to be
(19:53):
able to find all of thebenefits.
I think that utilities andgovernments communicate a lot
with their stakeholders.
And those communications aregenerally trusted.
And with just a little bit ofpersonalization, you can get
great engagement around thosecommunications.
The question then is (20:10):
is that
engagement working for you?
Are you going to be able tolook back and determine that, oh
yeah, there was this group ofcustomers located in this area
with a certain type of buildingthat showed outsize engagement
or outsize savings, or viceversa.
Is there are there segments ofmy population that are really
underperforming and pulling myaverages down?
(20:32):
Statistical analysis combinedwith data and combined with
really robust communicationdesign, I think uncovers some of
these hidden impacts.
And that's really, I think, thebig secret moving forward.
It's that there's so muchthat's happening.
If you think about a typicalutility service territory, let's
just say, let's just saythey're communicating with
(20:54):
100,000 meters every month via abill.
It's hard to imagine sendingout 100,000 messages a month and
that not having an impact.
And I think when you open youreyes to that potential, there's
a lot that's hiding in plainsight almost.
Ian (21:10):
There are certainly
segments of the utility customer
base that are very muchaccessible and receptive to the
traditional digital marketingmessages when they're tailored.
And then there are also,however, portions of the utility
customer population that areconsidered difficult to reach.
(21:35):
And I think sometimes it can beeasy to forget that there are
communities that utilities servewhere they maybe don't have you
know reliable access to aninternet-enabled device in their
home or they worknon-traditional hours.
So I'd like to talk maybe alittle bit about that.
(21:58):
And can you tell me some of thechallenges around getting the
customers engaged and thenactually enrolling them in
programs?
And how does that data thatwe're collecting, how does that
assist or transform engagementsfor those hard-to-reach
(22:20):
populations?
Alex (22:21):
This is maybe
controversial, but we don't
necessarily think abouthard-to-reach populations.
You know, our our goal is toour goal is to understand every
building, every consumptionprofile.
And and one of the things thatwe've learned that's really
interesting is that the thatdata is often independent from
(22:41):
engagement.
You know, so hard-to-reachcustomers may be hard to
communicate with, but we mayactually have a lot of
information about where they'relocated, what their buildings
are like, and and what potentialthey have for programs and
utility offers.
And and vice versa, you know,the the opposite can also be
true that sometimes it does workas you would think.
(23:02):
But when it comes down to it,you know, what we try to do is
come up with strategies thathelp us understand what's
happening in particularbuildings.
And then it's just a sort of atried and true process of
cycling through communicationstrategies and messages and then
having the ability to figureout which ones are actually
(23:23):
working.
You know, there's one thingI've learned is that there's no
silver bullet and and there's noparadigms, I guess, that that
can't be broken.
An example here would beprobably a home energy report
program that we ran recently.
And the sort of the adage abouthome energy report programs is
that they work best when thehome energy reports include a
(23:43):
certain type of message and aretargeted at a certain
population.
So if you use socialnormalization and you target
your relatively high-consumingcustomers, HER programs give
great results.
This story is about us notdoing that.
We we targeted the entirecustomer spectrum.
And what we actually found isthat when we tried different
(24:06):
message styles, we actually gotour low-consuming customers to
outperform the high-consumingcustomers.
So the customers that weren'tsupposed to be the ones that
generate the savings actuallygenerated the majority of the
savings, the most of thesavings.
And I think this gives peoplehope that, you know, these
customers that we thought weregoing to be hard to reach, these
(24:26):
low-consuming customers,they're gonna be hard to reach
with a home energy reportmessage, and they're gonna be,
it's gonna be hard to generatesavings from that population.
Well, what we found out is thatif you focus on fundamental
information, information aboutwhat's happening in their
building, you try differentmessage styles, you combine that
with other tried and truemethodologies, like we talked
(24:47):
about in the last example aswell, you can, you can actually
flip that paradigm of whichcustomers are hard to reach and
and which customers areconversely high potential.
I think that all depends on,you know, what are you talking
about, how are you talking aboutit, and how are you trying to
measure the results?
Ian (25:06):
So I think, yeah.
So if I could sum that up, itsounds like what you're saying
is that the avenue or thevehicle for the message really
is secondary or almost givenwhat really, you know, from a
data perspective matters more isthat the message is really
aligning with what you areseeing on the data side in terms
(25:26):
of both in terms of thereality, but also maybe what is
possible.
Is that correct?
Alex (25:31):
Yeah, definitely.
And I mean, we when we thinkabout it, we're we're thinking
about, you know, what is theoutcome that we want to drive?
We we want to drive, in thecase of the HER program, we want
to drive maximum behavioralsavings.
And so we went after customerswhere we thought there was high
potential.
And high potential is notnecessarily related to whether
(25:52):
or not a customer is easy toreach or not.
And and so I think again, byadding that additional context
into the picture, it can helpprogram managers and marketers
to rethink what it is they'retrying to do and be more outcome
focused as opposed to worryingabout I don't know, the makeup
of a customer base, for example.
Okay, that that definitelymakes sense.
Ian (26:12):
I think it's a helpful,
different way of looking at it.
And then engagement isobviously, as we're talking
about right now, is a big partof enrolling customers into a
program.
But the customer educationcomponent, maybe not the final
pitch, but just getting themaware whether that's aware of a
program, aware of a rate, or itcould even just be simple as
(26:37):
aware of their usage.
They may not even be aware oftheir usage.
What role does that play?
Are and are there other factorsin customer education that come
into play that has an impact onthese messages that you're
sending out, even if you haveall the right data?
Are there other things weshould be considering?
Alex (26:57):
I'm gonna sound like
Charles Dickens here.
Like education is criticallyimportant.
Ultimately, like that's that'sreally what we're trying to do.
And and and we define educationat Brilliant as inbound
customer experiences that aredesigned to drive customers to
take action.
The ironic part here is that Ithink that sort of like data,
(27:18):
these educational experiencesdon't have to be obvious to the
customer.
And more and more we'reeffectively seeing these edge
educational experiences probablygoing away.
Or maybe it's better to saythey're going to become more and
more embedded in the shortinteractions that we have with
customers.
And I think that's just a signof like the modern times, right?
(27:39):
Everything is getting snappier.
Everything, people, people'sattention span is not minutes,
it's it's seconds.
Ian (27:45):
And it's sometimes more
like integrating that micro
learning concept into all thecommunications that you're
doing.
Alex (27:52):
Exactly.
And how do you do that?
Well, you you do that byunderstanding your customers and
anticipating the types ofreinforcement they're gonna
need, the types of objectionsthat they're gonna have, and
that therefore you need toeliminate.
And that's almost what I thinkmodern personalization is really
about.
It's certainly not aboutparroting back to people, oh,
(28:15):
this is your name, this is youraddress, this is the type of
heating system we think youhave.
I think it's more aboutunderstanding, because of all
that, what is this person likelyto need?
What are they likely to havequestions about?
How difficult is this customerjourney gonna be for them to
walk down compared to othercustomers?
And then how do I embed in mycommunications things already
(28:39):
that are filtering out the idealcustomers from the people that
are really gonna struggle toparticipate?
Because chances are we don'twant them as participants
necessarily.
They're gonna be more costly toserve and they're likely to
have a more difficult time withthe program overall.
So this process of education isreally just it goes back to
again the outcomes that you'retrying to drive.
(29:00):
Understanding who your idealparticipants are, using the data
to get ahead of the concernsthey're likely to have, and
making those educationalexperiences embedded in these
microcustomer journeys that wecreate.
Ian (29:12):
You know, where I think
that really helps is you said
utilities and you customersgenerally already have, for all
intents and purposes, a highlevel of trust in their
utilities.
And I think being able to playthat role of providing the
relevant information at theright time, in the right context
with the right reinforcementsonly serves to really kind of
(29:33):
reinforce that.
But have you seen, whether it'squantitatively or
qualitatively, have you seen anyimpacts to that trust level
between the utility and theircustomers when you start using
the data in the way that you alldo this?
(29:54):
Have you seen any impacts inthat area?
Alex (29:57):
Yeah, man, I'm so
controversial today.
You know, like I I'm I'm whatwhat the thought that pops into
my head is like we don't careabout trust either.
You know, we don't we just careabout the outcomes that we're
trying to drive.
And so if you're trying todrive improved customer
satisfaction or reduced callcenter activity or cost savings
in some other part of thebusiness, then those metrics
(30:17):
become a proxy for, you know, doour customers trust us?
In general, there's lots ofgreat information about how this
type of approach, adata-driven, direct, focused
approach, builds trust.
We we look at that when when wedo certain like rate
explanation communications withcustomers.
(30:37):
And we'll ask them, do you feellike you now understand the
rate?
Do you feel like you need tocall into the call center and
ask more questions?
And in some cases, we'll evenask, how has your perception of
the utility changed because ofthese communications?
And and simply providingtimely, relevant communications
that are targeted to thecustomers that need them the
most.
I mean, the how that drivessatisfaction and perceived trust
(31:01):
of the utility is I was gonnasay it's immeasurable.
It's not, it's perfectlymeasurable.
I mean, you're getting 20 to50% improvements in those scores
after very short communicationcycles.
But again, I would I wouldchallenge that what we really
mean by trust is if we presentan offer to our customers, are
they willing to accept it?
(31:22):
Like that's trust in action.
And we don't have tonecessarily have the causation
there that, oh, they did thisbecause they trust us.
We're happy with just thecorrelation that we reached out
to this customer and then theytook this action.
And I think trust, you know, isit's an important thing to
think about in there.
But again, we're in a placewhere we have a lot of data, we
(31:44):
can get ahead of the needs ofcustomers, we can present them
with very relevant offers at theexact right time.
And trust is then evidenced byus achieving our targets.
Ian (31:53):
Yeah.
So certainly from yourperspective, you know, if you're
doing the right things, trustis kind of a given outcome of
what you're gonna get from theright data being implemented in
the right way to the rightaudiences.
It's a natural byproduct, itsounds like.
Alex (32:10):
Of course, yeah.
But but certainly I'm notsaying don't look for distrust,
right?
Like you have to, you have tomonitor, you have to be, you
have to be careful, you have toconstantly be measuring things.
So we, whenever we docommunication campaigns or
engagement campaigns, we'realways looking at, you know, how
many people are complainingabout this?
You know, how many calls to thecall center did we get?
Was there any negativesentiment?
(32:30):
How many people opted out ofdigital communications?
We're we're looking atreputation scores when we're
sending things out.
The fundamentals don't go away,obviously.
But absolutely, when whenthings are going right, reduced
complaints, I mean, it shouldreally go almost down to zero.
You'll you'll see these numbersdoing what they're supposed to
without you having tonecessarily focus on it because
(32:52):
you're focused on getting theright message to the right
customer, measuring all of theoutcomes and achieving your
targets.
Ian (32:58):
And many of our listeners
are involved in the
implementation and management ofutility customer programs, and
they may be responsible for theoutcomes.
So, what you know, what's onefinal piece of advice you can
give to those listeners for howthey can better help their
(33:18):
programs connect with thecustomers?
Alex (33:21):
I I think I would really
go back to that outcome focus.
Right.
I think that we we have so manyresources available these days
that it's tempting to fall intopatterns from taking it full
circle here, I guess, going back10, 15 years where mass
(33:43):
marketing communications werereally the only way.
And I think that what we havenow is an opportunity, the
systems are in place, theinfrastructure is in place.
I think even the utilitymindset is shifting.
Utilities more than everrecognize that they need to
provide their customers withchoices, and they also recognize
(34:04):
that their customers' choicescan have big impacts on things
that the utility cares about.
Customers are not justconsumers now, they can generate
their own energy.
Customers can make choices thatsignificantly change their
consumption patterns.
On the commercial side, we'reseeing data centers rising.
On the residential side, we'reseeing electric vehicles and all
(34:25):
these things that are reallyexpanding, not just contracting
the usage that customers arewanting.
And as you mentioned in theintro, we're now facing
challenges across the industryof demand actually being greater
than what we can readilysupply.
And so I think now more thanever, it's absolutely critical
(34:46):
that we think carefully aboutthe outcomes that we're trying
to drive.
And then we let data and toolsbe in service to those outcomes.
You know, we need to spend moretime, I think, understanding
the processes and the actionsthat customers need to work
through.
And this stuff is this stuffhas nothing to do with
(35:07):
technology or or data science.
It has everything to do withenergy expertise, engineering
knowledge, building scienceknowledge, program management
knowledge.
And so the experts within yourorganization are more critical
than ever.
So when we think about howshould we be implementing and
managing utility customerprograms today, it's really
(35:29):
about breaking down those silosthat we talked about before.
Let's get all the stakeholderstogether and let's deal with
everybody's concerns andoutcomes all at once.
Because as we talked about, youknow, there's definitely ways
to serve all the stakeholderswith single focus
communications.
And you can't do that if youdon't know what the outcomes are
that are most important.
And then once you know thoseoutcomes, then you can look
(35:51):
through all of your technologyresources.
You can look at companies likeBrilliant, and there's lots out
there like us who are here toprovide you with new technology
and services.
You can look within your ownteam, and I think you can start
to find that, again, the toolsthat you need to drive your
outcomes, like the outcomesthemselves in many cases, are
hiding there in plain sight.
(36:12):
The problem that we have todayis putting all the pieces
together quickly andintelligently to achieve our
goals.
I don't think that thechallenge that program managers
face today is like finding thenext new thing.
I think we have the tools, andit's just a matter of taking
advantage of that opportunity.
Ian (36:30):
Well, Alex, thank you so
much for that.
I think that was a great finalword of advice.
I appreciate you uh stopping byand talking with us today.
You really helped underscore, Ithink, the importance of the
utility-customer relationship,how the right data delivered at
the right time in the right wayreally can fundamentally change
the outcomes for utilityprograms.
(36:51):
And, you know, with with energycosts rising for the
foreseeable future, this isgonna be more and more important
as people talk more and moreabout affordability and
efficiency.
So I want to thank you forstopping by and talking with us
today.
That's it for this episode ofthe Energy Beat Podcast, and we
will see you next time.