AI in CRM: Initial and Hidden Costs, ROI, and Implementation Strategies

Transcript

welcome back to the Deep dive today

we're going to be tackling AI in your

CRM ooh it's a Hot Topic very much so

everyone's super excited about it and

you know what they should be they should

be it's exciting stuff but before we

jump in and everyone starts throwing AI

into their CRM mhm we need to talk about

the costs involved for sure and I'm not

talking about just that initial sticker

price right there's a lot more to it

absolutely and that's what we're going

to be uncovering today is like looking

beyond the sticker price of a car and

thinking about you know the insurance

gas maintenance yeah all that it all

adds up it really does so to guide us

through this we're going to be taking a

look at an article by CRM expert Jesus

Hoyos excellent article I thought so too

and it was so good that it even inspired

an episode of the Commerce DM konoyo

podcast oh very cool I'll make sure to

link that and the article in the

description perfect but we are going to

pack all of that here let's get into it

let's dive in let's start with why

everyone's so excited okay what are some

of those benefits that AI can bring to

your CRM we hear things like

personalization automation what else

well those are definitely the the big

ones you know AI can personalize these

customer interactions at scale you know

imagine tailoring every marketing

message every offer to each individual

customer's preferences and behaviors I

mean it's it's powerful stuff and it can

also automate those tasks like lead

qualification and data entry oh that

sounds wonderful yeah free up your teams

to focus on more strategic activities

instead of just those mundane things

okay and then of course Predictive

Analytics oh yes can't forget that one

huge huge AI can analyze your data to

forecast those future Trends identify

potential churn risks and help you make

those proactive decision so it really is

like having a crystal ball kind of yeah

in a way um but it's not all sunshine

and is it well you know it sounds like a

dream come true but there is a catch

yeah it's kind of like building a house

okay you know you got your initial

construction costs that are pretty

obvious up front mhm but then you've got

all those ongoing expenses you know like

maintenance utilities maybe a few

unexpected repairs down the line you

never know what's going to break you

never know exactly so okay so let's talk

about those initial construction costs

those upfront Investments for our CRM

what are we looking at there so first

you got the licensing fees for the AI

Solutions themselves okay some CRM

providers offer those native AI modules

you know they're convenient yeah but

often come with extra costs based on the

number of users the amount of data

you're processing okay or how much

customization you need so you're really

paying for what you get yeah and then

there are those external AI Frameworks

like those from open AI Google or AWS

right these can be really powerful but

they also come with their own pricing

models okay and usually that's based on

you know how much you use them how long

it takes to process the data makes sense

or you know other factors like that okay

so it's really important to pick the

right AI solution right from the get-go

yeah it is because it sounds like

there's a lot of options and you really

have to consider what's going to be the

best fit for you for sure it's kind of

like shopping for a car you know

different models different features

different price points exactly so you

have to think about well how much can I

afford yeah what do I need it for

exactly and then beyond that you know

once we've picked out our car yeah we

have to get it on the road we do yeah

what about integrating these AI

Solutions into our CRM well your spoton

integration costs are a significant

factor right especially if you're

dealing with a complex CRM system or

need some kind of special middleware to

bridge the gap between your AI tools and

your CRM like building a bridge exactly

it takes careful planning and the right

resources to make sure everything's

connected smoothly so it's not just

about buying a piece of software it's

like we're building this whole ecosystem

you got it and it all needs to work

together it does yeah okay so even with

a perfectly integrated system we're

still missing something okay we need a

place to put everything right oh yeah

where are we going to put it

infrastructure infrastructure yeah does

AI require anything special from our

Tech setup it absolutely does like what

AI especially when you're dealing with

that unstructured data oh yeah give me

an example of unstructured data like

text from customer emails okay or social

media posts right it's a data hungry

Beast oh boy this means you might need

to invest in more storage capacity mhm

potentially in the cloud okay and

depending on how complex your AI models

are and the volume of data you're

processing you might even need to

upgrade your Hardware to handle it oh

wow we're talking about things like

powerful processors right maybe even

specialized graphics cards wow designed

for AI workloads it's a whole different

world it is okay so to sum up we've got

the cost of the solutions themselves MH

we've got the cost of integrating those

Solutions into our CRM and then

potentially upgrading all of our

infrastructure to be able to handle all

of that data and all of that power

exactly and that's just the tip of the

iceberg oh no we're just getting started

just getting started because Jesus

mentions hidden costs in his article

what are those well the hidden costs are

where things get really interesting and

potentially more challenging to budget

for oh these are the less tangible

expenses that often get overlooked but

can significantly impact your overall

investment yeah what well one of the

biggest hidden costs is data quality

data quality data quality why is that so

important AI relies on clean and

accurate data to function effectively

okay that makes sense if your data is a

mess full of Errors inconsistencies and

missing values your AI models just won't

be able to do their job properly garbage

and garbage outright exactly it's like

trying to bake a cake with rotten eggs

yeah it's just not going to work it's

not going to work no so what can we do

about that well you might need to invest

in data cleaning and enrichment tools

okay these tools can help you identify

and correct errors fill in missing

values and standardize your data formats

so these tools are basically like our

data Butlers yeah kind of they're

cleaning up after us making everything

nice and tight and organized exactly

making sure everything's in its right

place okay we got data quality anything

else another big one is data and AI

governance governance governance right

as AI becomes more integrated into our

businesses we need to make sure that

we're using it responsibly and ethically

of course of course this means complying

with privacy regulations like gdpr right

establishing those clear guidelines for

data usage and addressing potential

biases in our AI model wow ethics

regulations that's a lot to consider it

is and those are important very but they

also sound expensive they can be yeah so

what kind of Investments do we need to

make here well you might need to invest

in governance tools that help you track

data lineage manage consent and ensure

compliance with relevant regulations

okay you also might need to develop

internal policies and procedures for

data usage and AI development and you

might even need to hire specialized

personel

like who like data ethicists wow or AI

governance experts to guide your efforts

okay it's an emerging field and staying

ahead of the curve is crucial so we're

really laying the foundation we are yeah

for the future of AI yes but it's not

cheap it's not but it's an investment it

is worth making Okay so we've got data

quality we've got

governance what else is lurking in the

shadows well you're right there are

quite a few okay another hidden cost is

training in or organizational change oh

right people people yes we can't forget

about the people no we can't

implementing AI often requires

significant changes to workflows

processes even job roles you need to

train your team to use these new AI

tools effectively of course and you also

need to manage any resistance to change

that might arise oh yeah I can imagine

some push back there definitely yeah

some people are comfortable with the way

things are right and they don't want to

rock the boat right but it's important

to bring everyone along on the journey

exactly and make sure they understand

the benefits of AI so what are some

strategies for smoothing out that

transition well communication is key

okay you need to clearly articulate

those benefits of AI address any

concerns proactively and involve your

team in that implementation process so

it's about getting Buy in it is yeah

makes them feel like they're a part of

it right that this is not just some top-

down decision but that we're all in this

together exactly okay well even with you

know a well-trained team and everyone's

on board and excited about AI we can't

forget about the bigger picture that's

right and the CRM system itself yeah how

does it fit into our overall technology

you need to make sure that your CRM

system is robust and flexible enough to

support AI integration yep you also need

to consider things like Omni Channel

consistency wait hold on Omni Channel

consistency what is that it means

ensuring a seamless and consistent

customer experience okay across all

those channels give me some examples of

channels whether it's your website

mobile app social media or physical

store AI can play a huge role in

achieving this okay but you need to make

sure your CRM system can integrate with

all these different touch points it's a

lot it is yeah okay so the CRM is like

the central Hub yes that connects all of

these different channels and it's

bringing in all this data exactly it's

like the brain of your customer

operations wow but what if our CRM isn't

to Snuff well that's a real possibility

you might need to invest in upgrading

your CRM system MH or even consider

migrating to a more modern platform

that's designed with AI in mind wow okay

so it's really this you know it's all

connected it is very interconnected yeah

and if one piece isn't working right the

whole system can fall apart pretty much

so we've got licensing integration

infrastructure data quality governance

training M CRM upgrades and Omni Channel

consistency it's a lot to juggle it is

my head is spinning I know it can be

overwhelming and we haven't even talked

about the different pricing models that

AI vendors use I feel like we've just

opened Pandora's Box we have but don't

worry we'll break it all down in the

next part of our Deep dive okay okay

we'll demystify the world of AI pricing

models explore strategies for measuring

the value of your AI investment yeah and

even dive into some real world examples

to bring it all together I am so ready

for that I think you're going to like it

I think too but for now we're going to

have to leave it there sounds good we

will be back after a quick break to

untangle those pricing models can't wait

and help you navigate the AI cost

landscape with confidence so stay tuned

we'll be right

back welcome back to the Deep dive

before the break we were really getting

into the nitty-gritty of AI costs in CRM

yeah my head was spinning a little bit I

bet we've covered so much from those

licensing fees and integration costs to

you know data quality and governance

right we even touched on Omni Channel

consistency we did but now I'm curious

about how do AI vendors actually package

all this how does it actually work from

like a business perspective what are the

different pricing models we might

encounter that's a great question

understanding those different pricing

models is crucial for making those you

know informed decisions and ensuring

you're not hit with unexpected costs

down the road right it's kind of like

choosing a mobile phone plan you know

okay you've got your pays you go options

you've got your unlimited data plan

everything so many choices so many

choices each model has its pros and cons

so you need to carefully consider your

needs and your usage patterns okay

starting to see the analogy here so

let's break down these AI pricing models

what are some of the most common ones

that we should be aware of one popular

model is usage based pricing okay this

is where you pay for what you use

similar to you know how you pay for

electricity or cloud storage good it can

be a good option for those pilot

projects or when you're first dipping

your toes into AI because you're only

paying for the resources that you

consume so it's kind of like a pay as

you go model exactly sounds appealing

for those early stages when you're not

really sure how much you're going to use

it how much you'll need right but are

there any downsides well the biggest

challenge with usage-based pricing is

predictability okay your costs can

fluctuate depending on your AI usage

which can make budgeting difficult right

because you don't know month to month

what you're going to be spending exactly

you know if you suddenly experience a

surge in customer interactions or need

to process a large volume of data you're

AI cost could Spike unexpectedly not be

good no especially if you're on a tight

budget yeah it's a little bit of a

gamble it is a bit of a gamble yeah you

might save money if your usage is low

right but you could also end up with a

hefty Bill if your AI needs suddenly

increase so what are some other pricing

models that maybe offer a bit more

predictability another approach

approaches value based pricing okay this

is where the price is tied to the

perceived business value that the AI

solution delivers what does that mean so

for example an AI vendor might charge

you a percentage of the revenue increase

you achieve oh wow or a fee based on the

number of leads generated by their AI

powered marketing campaigns so they're

basically saying we're so confident in

our AI that will only charge you if it

delivers results exactly it's a bold

claim it is but but how do you actually

measure that value you're right

measuring value can be tricky right and

it often requires a close collaboration

between you and the AI vendor to define

those clear kpis and establish a

methodology for tracking results okay so

a lot of communication involved yeah a

lot of communication so value based

pricing requires a lot of trust and

transparency on both sides it does you

need to be confident that that AI vendor

can deliver on their promises and they

need to be able to demonstrate the value

that they're providing it's a

partnership it is so what about

something a little more straightforward

okay are there any pricing models that

offer a fixed predictable cost

absolutely a common model is

subscription-based pricing where you pay

a fixed monthly or annual fee for access

to those AI features okay this is

similar to how a lot of those software

as a service sauce products are priced

makes sense it offers predictability and

it simplifies budgeting which can be a

big Advantage for those businesses that

are looking for cost stability so

subscription based pricing that sounds

familiar it's like my Netflix

subscription or my Spotify I pay a fixed

fee every month and I get to access all

the features and content exactly within

that subscription tier are there

different tiers for AI Solutions yes

many AI vendors offer tiered pricing

models this is where you choose a

subscription tier based on your

anticipated usage needs the number of

users or the level of features that you

require okay lower tiers typically offer

basic functionality at lower cost okay

while higher tiers provide more advanced

features higher data processing capacity

or dedicated support So tiered pricing

gives you some flexibility and control

over your costs it does you can start

with the basic tier and then scale up as

your AI needs grow exactly but what

happens if you outgrow your current tier

can you easily switch to a Higher One

usually yes most AI vendors allow you to

upgrade or downgrade your subscription

tier as needed okay however it's

important to understand those terms and

conditions right as some vendors might

have minimum contract lengths or early

termination fees always read the fine

print always read the fine print yeah

Okay so we've got usage based value

based yep subscription based and tiered

pricing MH is there anything else we

should be aware of any other kind of

wild and crazy pricing models out there

well there's one more model that's

becoming increasingly popular especially

for those AI solutions that involve

significant data processing and training

okay it's called Data Cloud pricing data

Cloud pricing what is that think of data

clouds as these specialized Cloud

platforms that are optimized for AI

workloads okay they provide access to

pre-trained AI models massive data sets

and Powerful Computing resources it's

like a One-Stop shop it for all your AI

needs exactly what about the pricing

well the pricing for data clouds is

often based on a combination of factors

like what including the amount of data

you store the compute time you use for

training your AI models and the number

of API calls you make to access those

models so you're really paying for what

you use but on a much larger scale yeah

you are it sounds really convenient but

I imagine it could get expensive it can

yeah data Cloud pricing can be very cost

effective if you're leveraging those

pre-trained models and readily available

data sets right but if you're building

custom AI models from scratch and need

extensive training yeah the costs can

quickly add up it's like anything you

know if you want the custom stuff it's

going to cost more exactly okay so we

really need to be strategic about how we

use data clouds we do and think about

those trade-offs between convenience and

cost exactly Okay so we've got a pretty

good understanding of these different

pricing models we do but now how do we

actually decide which one is right for

us choosing the right pricing model is a

critical decision right it should align

with your business goals your risk

tolerance and your anticipated AI usage

patterns that's a lot to consider it is

but it's important to think about all

these things up front right you know if

you're just starting out with AI and

want to experment without a large

upfront commitment right usage-based or

a low tier subscription model might be a

good starting point so start small start

small scale up as needed exactly what

about companies that have more

established AI initiatives and are

looking for predictable costs for those

companies a fixed fee subscription or

even a value based model might be more

suitable okay but remember with value

based pricing you need to have a solid

grasp of your kpis right and the ability

to accurately track the return on your

AI investment that brings up a really

good point we've talked a lot about the

costs of AI but how do we actually

measure the value that it brings how do

we know if we're getting a good return

on our investment that's where those two

trusty metrics we mentioned earlier come

in okay total cost of ownership TCO and

return on invest

Ro okay TCO and Roi can you give us a

quick refresher on what those are and

how they apply to Ai and CRM absolutely

TCO is a holistic view of all the costs

associated with implementing and

maintaining an AI solution throughout

its life cycle so it's not just that

initial sticker price no it goes beyond

that initial purchase price and includes

things like licensing fees integration

expenses infrastructure costs data

preparation training governance right

and ongoing maintenance okay it's really

the whole picture it is it's like

calculating the total cost of owning a

car okay including not just the purchase

price but also you know Insurance gas

repairs and depreciation so TCO gives us

a complete picture of the financial

commitment required for AI it does go

about ROI ROI is a way to quantify the

financial benefits you're getting from

your AI solution okay it's typically

calculated as the net profit or cost

savings generated by that AI solution

okay divided by the total cost of the

investment okay so how much are we

actually making or saving exactly it's

like figuring out how much money you're

making from that car you bought you know

maybe by using it for ride sharing or

delivery services and comparing that to

the total cost of owning and operating

the vehicle okay so TCO is like the full

cost and then Roi is like are we

actually making money are we saving

money exactly are we getting a return

but how do we actually calculate these

metrics in practice you're right

calculating TCO and Roi for AI can be

complex but there are tools and

methodologies that can help and we'll

dive into those in the next part of our

Deep dive and we'll even look at some

concrete examples to bring these

Concepts to life sounds good I'm really

eager to see how those calculations work

in real world scenarios because I think

that's where it really clicks for people

yeah absolutely so stay

tuned welcome back to the Deep dive

we've been on this Ai and CRM journey

and honestly it's a bit of a financial

maze it can be we've talked about the

costs The Upfront the hidden those

sneaky little things and even the

different pricing models yeah but how do

we actually measure the value right how

do we know if it's worth it exactly

that's where those two trusty metrics we

talked about earlier come in TCO and Roi

right total cost of ownership and return

on investment they're like our financial

Compass they are guiding us through this

jungle yeah but how do we actually use

them in real world situations yeah can

we walk through some examples absolutely

let's start with

marketing imagine you're a retail

company mhm okay looking to personalize

your marketing campaigns mhm boost those

conversion rates sounds good you've

decided to invest in an AI solution that

can analyze customer data segment your

audience and tailor your messaging it's

all about personalization these days is

so how do we actually calculate the TCO

for this well you need to factor in all

those costs we discussed earlier the

licensing fees for the AI software any

integration expenses to connect it to

your CR M maybe some additional data

storage costs if you're dealing with

large data sets Okay and don't forget

about those hidden costs like training

your marketing team right the people

costs exactly okay so it's like a

checklist make sure we've got everything

yeah got all those expenses both the

obvious and the hidden ones okay so

let's say we've done our due diligence

okay we've calculated our tcco let's say

it's $50,000 for the first year okay now

the big question is a worth it how do we

measure the

ROI to calculate the ROI you need to to

compare that $50,000 investment to the

financial gains generated by those AI

powered marketing campaigns okay so

let's say hypothetically our AI solution

helps us increase email open rates by

20% click-through rates by 15% wow and

ultimately leads to a 10% boost in sales

conversions those are some impressive

results they are but how do we turn

those percentages into dollars that's

where your sales data comes in you need

to analyze how much revenue those

additional conversions are generating

okay let's say your average sale value

is $100 okay if your AI powered

campaigns lead to an extra hundred sales

per month that's an additional $10,000

in monthly revenue or

$120,000 per year okay I see where

you're going with this $50,000

investment $120,000 return exactly to

calculate the ROI we simply subtract the

investment cost from the revenue gain

and divide that by the investment cost

so in this case the ROI would be 120,000

minus 50,000 / 50,000 which equals 140%

140% Roi 140% Roi that's amazing it is

it shows you the power of AI when it's

done right so AI can clearly Drive

Revenue growth it can but what about

other areas of the business can we use

these same principles for sales or

customer service absolutely the

principles are the same but the specific

metrics might differ depending on the

application

let's take sales as an example imagine

you're a software company with a large

sales team and you're looking to improve

their efficiency and close rates who

isn't exactly so you decide to implement

an AI powered sales assistant that can

help your reps prioritize leads schedule

meetings and even provide real-time

coaching during sales calls it's like

having a little AI coach in your pocket

kind of like that yeah so how do we

quantify the benefits how do we

calculate the ROI for this again you

need to identify those key metrics that

matter most to your sales team like what

things like lead conversion rates

average deal size sales cycle length and

of course overall revenue generated the

things that matter the things that

matter exactly and let's say your AI

sales assistant helps your team shorten

their sales cycle by 10% increase their

lead conversion rate by 5% and close

deals with a 2% higher average value

okay those are some big numbers they are

and you need to analyze your historical

sales data and project how those

improvements will impact your bottom

line right because percentages are great

but we need to see how it actually

affects the money exactly right so let's

say your average deal size is currently

$10,000 okay a 2% increase would mean an

extra $200 per deal okay if your sales

team closes 100 deals per year that's an

additional $20,000 in Revenue nice add

to that the revenue gains from the

shorter sales cycle and the higher

conversion rate and you can start to see

a substantial return on your AI

investment it all adds up it does okay

so again identify the key metrics track

of the improvements and then translate

those into actual Financial gains yeah

okay what about customer service can AI

help us improve customer satisfaction

absolutely AI is transforming the world

of customer service in what ways well

let's say you're an e-commerce company

with a high volume of customer inquiries

mhm you decide to implement an AI

powered chatbot on your website to

handle those frequently asked questions

freeing up your human agents to focus on

more complex issues okay chat Bots

they're everywhere but how do we

calculate Roi for something like

customer

satisfaction you're right customer

satisfaction can be tricky to measure

yeah but there are ways to quantify it

like what you can track metrics like

customer satisfaction scores CSA oh net

promoter scores NPS and even customer

turn rates okay so if our AI chat but

can successfully resolve those customer

issues reduce weight times improve

overall satisfaction we'll see those

metrics improve exactly a happier

customer is a more loyal customer makes

sense they're more likely to stick

around right and spend more money

exactly and by automating those routine

inquiries with a chatbot you can reduce

the workload on your human agents

potentially allowing you to reduce

Staffing costs or redeploy those agents

to more strategic tasks so we can free

up our human agents to actually do the

things that require that human touch

exactly the things that AI can't do yet

right and then when you have happier

customers you also get better reviews

yeah more referrals word of mouth is

powerful it really is it can really

boost your brand reputation and attract

new customers it's like a positive

feedback loop it is AI is giving us

happier customers which is leading to

more revenue and a stronger brand and it

just Builds on itself exactly AI in CRM

is not just about implementing cool

technology it's about using that

technology strategically to solve

business business problems improve

efficiency and ultimately Drive Revenue

growth and Customer Loyalty so for our

listeners who are maybe thinking about

Ai and

CRM what are some key takeaways what

should they remember as they embark on

this journey first don't get caught up

in the hype AI is not a Magic Bullet

it's crucial to have a clear

understanding of your business

objectives and how AI can help you

achieve them so start with a strategy

start with a strategy not just a

fascination with shiny new tech wow

second carefully evaluate the costs

involved remember those hidden expenses

we discussed Factor those into your

calculations and make sure you have a

realistic budget for implementing and

maintaining your AI solution AI is an

investment it is and we need to treat it

as such we do what's our third takeaway

third choose the right pricing model we

explored several options from usage

based to Value based and subscription

model select the one that aligns best

with your usage patterns your risk

tolerance and your long-term business

goals right think about those long-term

goals yeah don't just focus on the

shortterm exactly what's our fourth

takeaway fourth measure measure measure

don't just assume that AI is working its

magic track those key performance

indicators kpis calculate your TCO and

Roi and continuously evaluate the impact

of AI on your business data is King data

is King we need to let that guide us Let

It Be Your guide okay any final words of

wisdom AI is a powerful tool that can

trans transform your CRM and your entire

business but like any tool it's only as

good as the person wielding it right so

be strategic be data driven and embrace

the possibilities that AI offers and

remember the world of AI is constantly

evolving so stay curious keep learning

and never stop exploring that's a great

note to end on thanks for joining us on

this deep dive into Ai and CRM it was my

pleasure we hope you found it insightful

and empowering and remember knowledge is

power it is so keep exploring keep

learning and keep pushing the boundaries

of what's possible with AI

AI in CRM: Initial and Hidden Costs, ROI, and Implementation Strategies

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