Technology Partners

Our Team

Our Awards

A team of people smiling and holding up their hands while holding paintbrushes

Social impact hero

Social Impact

Newsroom

Careers

About Us

Contact

Do Not Sell my Personal Information

Cookie Preferences

Culture Value Chain

iLabs Center for Innovation

Industries

Insights

Investor Relations

Locations

TELUS International is a subsidiary of: 

Privacy Shield Framework

Customer Privacy Policy

Solutions

Website User Terms

Icon twitter

Icon facebook

Icon youtube

Icon linkedin

Technology

Financial Services & Fintech

Automotive

Healthcare

Communications & Media

Games

eCommerce

Travel & Hospitality

hero bulgaria locations

Bulgaria

A man in a brightly lit room smiling while on his phone

hero guatemala locations

Guatemala

hero romania locations

Romania

hero india locations

India

hero china locations

China

hero us locations

United States

Spain-Hero

Spain

hero philippines locations

Philippines

hero ireland locations

Ireland

Cityscape with Galata Tower and Gulf of the Golden Horn in Istanbul, Turkey.

Hero Türkiye Locations

Türkiye

hero el salvador locations

El Salvador

germany-hero

Germany

Europe-Hero

Additional European Centers of Excellence

infobrief

Guide

Resource Type Article

Article

case-studies thumb

Case Study

whitepapers thumb

Research & Reports

checklists thumb

Checklist

brochures thumb

Brochure

ebooks thumb

E-book

Podcast Type Image

Podcast

Discover the benefits of intelligent automation and how humans and digital coworkers are working together to achieve business optimization.

Colorful datapoints forming the shape of a human face

humans automation

What happens to humans after we automate?

Squeeze every drop of value out of your cloud deployment with tips on overcoming common challenges and optimization.

Vault in the shape of a cloud meant to symbolize unlocking the full value of the cloud

cloud unlock

How to maximize the full value of the cloud

Artificial intelligence is set to define the future of banking. Learn about how banks are using machine learning, RPA and other AI-powered tech.

banking ai

Six AI technologies set to define the future of banking

Risk mitigation should be a top consideration when selecting an outsourcing partner. Learn what to look for to ensure your brand is protected.

3D illustration of various symbols conveying online security, including a finger print and a shield 

protecting brand

Protecting your customers and brand in an outsourced environment

A copy of the Digital customer experience priorities in 2023 report on top of a green leafy plant.

Digital Customer Experience Priorities 2023 Preview Image

TELUS International, in partnership with Statista, surveyed 250 enterprise leaders to explore where they plan to invest in digital customer experience (CX) technology in 2023. Uncover the results.

An illustrated representation of customer profiles and leaving a five-star review online.

Digital Customer Experience Priorities 2023 Hero

Survey results: Digital customer experience priorities for leaders in 2023

IDC Info Snapshot - Cloud thumbnail

Uncover the advantages of partnering with a trusted advisor to create and deliver your cloud vision in this IDC Info Snapshot.

IDC Info Snapshot - Cloud hero

IDC info snapshot cloud feature image

Partnering with a managed service provider can help companies achieve agility, scale, and business value with cloud

The digital world continues to shift rapidly. Discover what's next for content moderation to help you navigate the changes in this evolving industry.

Illustration of a robot and human working together, symbolizing the future of content moderation

Blog-post5-What-s-Next-for-Content-Moderation

What's next for content moderation in 2023 and beyond?

Upgrading a computing environment with TELUS International's Mainframe Cloud Services

Explore how TELUS International's Managed Cloud Services provide flexibility, cost efficiency and enhanced security and control.

Image of computer screen with cloud on it

Upgrading a computing enviroment - feature image

A copy of the outsourcing locations e-book on a white tablet on top of a green fern.

Outsourcing Locations E-book Feature

Discover some of the top outsourcing destinations for consideration and the factors to keep in mind as you make your decision.

Feature-Landing-Image Locations Outsourcing

Selecting the best outsourcing destination for your business

A preview image of the case study document overlaying green grass.

Streamlining operations and kickstarting the digital transformation journey - preview image

Uncover how TELUS International’s business process consultants helped a leading financial services brand optimize its operations, enhance its customer experience (CX) and begin its digital transformation journey.

Happy customer support agents sitting at computers and speaking on headsets.

Streamlining operations and kickstarting the digital transformation journey - feature image

Streamlining operations and kickstarting the digital transformation journey of a leading financial services brand

Customer experience analyst and best-selling author, Matt Dixon, sits down with TELUS International Studios to share insights from his new book, The JOLT Effect: How High Performers Overcome Customer Indecision. Dixon takes us through the bane of every salesperson’s existence: a long customer courtship that ends with an “I’ll think about it.”

Leveraging a first-of-its-kind study that analyzed 2.5 million documented sales conversations through machine learning, Dixon reveals that 56% of sales loss is actually caused by customer indecisiveness. Listen to the episode to gain more sales growth best practices to overcome indecision.

To learn more about TELUS International and our digital CX solutions, contact us today.

The JOLT Effect: How high performers overcome customer indecision is available for pre-order now.

Intro: TELUS International Studios, where customer experience meets digital transformation.

Patrick Haughey (PH): And you are very welcome back to TELUS international studios. I’m your host Patrick Haughey, and on this episode I am delighted to be joined by someone who I’ve had the pleasure of speaking with at a few TELUS International events over the last couple of years. Matt Dixon is a CX and sales expert, he has written many best-selling books — one of the best known is The Effortless Experience, but he’s joining us on this episode to talk about his newest book, currently available for pre-order. It’s called The JOLT Effect: How High Performers Overcome Customer Indecision. To prepare for this book, 2.5 million documented sales conversations were studied using machine learning. So get ready to hear some very interesting insights from this first of its kind study. So I thought an interesting jumping off point with Matt might be a line that jumped out at me from the book’s description when I was reading it. And that line reads: “In sales, the worst thing you can hear from a customer isn’t ‘No,’  it is ‘I need to think about it.’ And I started by asking Matt why this is.

Matt Dixon (MD): Yeah, it’s a great question. That’s the beginning of the whole tale. And I love that line, too. Well, I don’t love it: I hate it — it’s terrible, it’s really bad news actually, for sales people. But it speaks to what the whole story is about. You know, I think if I’ve been out there engaged with sales people, I know, obviously, Patrick, you and I have spent a lot of time talking about customer experience, customer service, the effortless experience, etc. The other hat I’ve worn as a researcher is really focused on business to business sales and commercial effectiveness, and how is buying behavior evolving and so on and so forth. And one of the things I’ve been struck by over the years is that when you ask a roomful of salespeople to think about the deals they’ve lost over the past quarter or the past year perhaps, and you ask them to categorize that into two different buckets. On the one hand, deals you lost to a named competitor. So the customer ends up buying but they didn’t buy from you, they bought from somebody else. Versus customers where you lost, but you didn’t lose to a competitor, you lost to no decision — you lost to the customer doing nothing. What you find is, in organization after organization, by far more hands go up around the latter, that salespeople feel like they’re much more likely to lose to the customer doing nothing than buying from a competitor or, as you said, even just saying no.

MD: In fact, I think sometimes in sales we can feel like our sales people are heavily influenced by the last sales call they had, you know the product is too expensive, this competitor is eating our lunch, whatever it is. But in this case, our salespeople are actually onto something. We studied this with data and we’ll talk more about the research that went into the book, but I’ll pull forward one finding, which is that anywhere between 40 and 60% of all deals are actually lost to no decision, to the customer doing nothing. And we studied this across 2.5 million sales conversations. We used machine learning to study it. And what we found is exactly what you said. If you look at all of the I would say hundreds of thousands of things that are said in sales conversations, both on the salesperson side and the customer side, by far in our analysis, the worst thing that can be uttered by the customer is I need to think about it. And the reason it’s so bad is that, you know, the old adage in sales has long been that as a salesperson, you don’t want to you don’t want to chase garbage trucks, right? You don’t want to pursue opportunities that have no chance of closing. So in many respects, for a salesperson, it’s far preferable — it may be painful — but far preferable to be told no. The worst outcome is where you go through the entire sales process with the customer. For many companies that can be months or even years, and think about all the resources, the time investment from the salesperson side, the resources from their organization, not to mention all the resources from the customer side. These are customers who go through the demo, they go through multiple iterations of the proposal, they talk to your reference clients, they talk to your subject matter experts, you talk to all of the sales prevention departments inside the customer organization like legal, finance, procurement, etc., only for the customer to get cold feet late in the game and end up doing nothing. And so that is such a deadweight loss for the average salesperson, for sales managers and teams and for entire sales organizations. We do think that how to overcome that ‘no decision’ phenomenon, how to break through and pull more deals across the finish line is the thing that separates great sales organizations and great salespeople from the rest.

PH: We’re going to come to those traits of a great salesperson who can manage to overcome the hurdle in a few minutes’ time, because it’s a fascinating area. We’re looking at something very psychological here called omission bias. Is that right? Which you cover a little bit in the book. Just briefly explain what omission bias is and what kind of mistakes customers are looking to avoid.

MD: Yeah, perfect. So I think the conventional wisdom in sales has always been that if the salesperson starts to get cold feet, if they start to backpedal, wring their hands a bit, waver, waffle, straddle the fence, whatever term you want to use, that it must be that we’ve not we haven’t put to rest the status quo, because we all know, even as human beings, we are predisposed to stay the course. We’ll pass up on better options just for no other reason than we’re lazy and we don’t like to change. And for salespeople, that’s a really powerful obstacle. But I think salespeople have always been taught that that is your only enemy in sales. And what we found was that in our analysis of 2.5 million sales conversations, when this customer starts to show signs of hesitancy, when they start to show those signs of cold feet, by far, three-quarters of salespeople we found go back and they kind of hammer the status quo. They either try to re-convince the customer that ‘you must not really understand the value that our solution is going to deliver.’ ‘You must not really understand how wonderful it is, the ROI projections and how amazing things are going to be on the other side.’ Or, when the customer doesn’t respond to that, what do we do? We put away the carrot and we break out the stick. And what we try to do is show the customer the cost of inaction. And we do that by dialing up what’s called FUD in sales: fear, uncertainty and doubt.

And what we’re really trying to do is make the customer squirm a bit, make them feel the pain of what they’re going to miss out on if they don’t if they don’t buy the solution. We actually found in the analysis, surprisingly, is that that approach, while it’s commonly practiced, actually makes it 84% less likely you’re going to get the customer out of no decision. So you actually increase the odds of the customer doing nothing by using some of those tactics designed to beat the status quo. And to your question, what we actually found, we realized that we wrestled with this quite a bit because it’s been the conventional wisdom in sales for a very long time. In fact, we wrote about this in the Challenger Sale that the best salespeople are gifted at showing the customer that the “pain of same,” the pain of the status quo is actually worse than the pain of change. And that is one of the things they do really well. And so it came as a big surprise to us that that strategy, that approach backfires so often. And so we took a step back and what we realized was we were asking the wrong question. The question that we were asking was, what’s the best way to beat the status quo? Maybe it’s just not being done well. Maybe high performers have figured out a different technique that’s really effective today. But the question we should have been asking is a bit different, which is not how do we beat the status quo, but rather why do customers make no decision? And it turns out the reason they make no decision is exactly what you talked about, Patrick, actually if you look at the psychology research and this is actually backed up in our own analysis, that there are really two reasons the customer will choose to do nothing. The first reason is that they’re committed to their status quo, they just prefer the status quo. It could be that they don’t believe your solution is superior to what they do today or they may just believe it’s superior, but they believe their current approach is good enough. Right? ‘It’s just not worth it for us to change.’ But there’s a second reason that the customer will choose to do nothing. It’s not commitment to the status quo, it’s indecisiveness about changing the status quo. And I think when people hear that, what they immediately ask is, how are those two things different? You’re telling me that customers choose to do nothing either because they prefer what they do today or because they don’t want to change what they do today. And what we explain in the research is that those two things are massively different. And it’s something that high performers get an average performance don’t.

MD: So if we go to the psychology research, what we find is that there are really two types of loss that people in our customers are worried about. On the one hand, there are what are called errors of omission, which are mistakes and losses that we incur because we choose to do nothing. One of the old stories to illustrate is you’re in a tennis tournament and your competitor has a peanut allergy and you sit down to enjoy a lunch before your match and you know there’s something on the menu that has peanuts in it. The omission bias is when your competitor orders the dish that has peanuts in it and you don’t say anything about it. And so they get sick and they have to drop out and you win. The opposite is an error of commission. Now, an order of commission is when you incur a loss because of something you did, not because you failed to do something right, but because you actually did something wrong. So the same metaphor uses you’re sitting across the table from your tennis competitor and you proactively suggest they order the thing that has peanuts in it because you want them to get sick. Now, with those two scenarios, the outcome is exactly the same, your competitor has gotten sick and had to be rushed to hospital, etc. But by and large, everyone was more comfortable with the first one because I didn’t have anything to do with it. The second one is ‘a thing I did.’ ‘I did something wrong.’ And what we find with customers is that when they’re facing two different options, whenever something could go wrong by me not choosing to buy your solution, we could not capitalize on an opportunity, or I could buy your solution, and then something bad could happen as a result, they will choose to do nothing far more often than they’ll choose to do something and run the risk of getting something wrong. Now, the three types of things they’re worried about getting wrong are:

MD: One, I picked the wrong option. We think about all the options we put in front of our customers. So often they start to wring their hands about, ‘I’m not sure if I’m picking the right contract length’ or the right scope of the agreement or ‘I’m buying the premium version — should I really just buy the basic version?’

MD: The second thing is they start to worry that they haven’t done enough research and think about all the content out there about every vertical, every technology out there. And they start to fret over the fact that it’s the next white paper that they would consume that will have all the answers that they need to be a smart consumer.

MD: The third source of indecision is what we call outcome uncertainty. This is where the customer, before they sign on the dotted line, starts to worry that they don’t have any assurance that they’re going to get the benefits they’re paying for. And despite your rosy ROI projections, despite the great demos and proof of concept trials you did, despite the wonderful reference calls and the great analyst reports they read about your company, the customer is worried that they might be the one company for whom this whole thing goes sideways and if that happens, somebody’s head is going to roll. And the person who is going to roll first is the person whose name is on the contract.

MD: So those three things: I’m picking the wrong option, I didn’t do enough homework, or I’m going to be left holding the bag (if you will) and not getting what I’m paying for, are the sources of indecision, which interestingly have nothing to do with the customer’s preference for the status quo. And so it helps explain why we see this phenomenon that salespeople who are taught that every indecisive customer, every waffling and wavering customer with cold feet, must be struggling with a preference for the status quo. So you go back and, you know, your ‘beat the status quo playbook’ is like a hammer, every indecisive customer looks like a nail. But in fact, if they’re worried about something else, then going back and trying to convince them of the loss that might result from inaction only gives them more to be worried about when they’re actually worried about something quite different. So we found in the research that high performers have figured out a different playbook, a companion playbook not just for beating the status quo, but for laying to rest or overcoming these sources of customer indecision.

PH: And does this take us to the JOLT effect?

MD: Absolutely, yeah. So what we found is, there’s again, there’s two playbooks. We’ve all got ‘the beat the status quo’ playbook. We wrote a book about challenger selling; we happen to think being a challenger is one of the best ways to beat the status quo. But as I said before, it’s only part of the story. If beating the status quo is all about showing the customer the cost of inaction, overcoming indecision is getting them more comfortable with the action you’re asking them to take, making them feel like you’re making a good choice, don’t worry about the other options, you’re picking the right thing. You’ve done enough research, you’re in good hands. I’m your subject matter expert, your trusted advisor, and don’t worry, you’re not jumping out of a plane without a parachute. There are some assurances we can give you that this is going to actually work out well for your organization, etc. So if the beat the status quo playbook is about dialing up the fear of not purchasing with the customer, then the playbook for overcoming indecision is about dialing down the fear of purchasing, right? It’s making the customer more confident and comfortable in the decision you’re asking them to make, which they are quite anxious about, right. I didn’t do enough homework. I’m picking the wrong thing. I don’t have any assurance this is going to work out for me. And so JOLT is a set of four behaviors, and I’ll just explain what they are really quickly, that together form this playbook for overcoming indecision:

MD: The J is judging the level of indecision. And what we found is that high performers are quite good not just at assessing opportunities and customers on their ability to buy their solution, but also on their ability to make a decision. So not just the ability to buy, but the ability to decide. And they do that through active listening, probing questions, and powerful requests they make that elicit responses from the customer that tell them, ‘Is this person somebody who can actually make a decision and do so in a reasonable amount of time?’

MD: The O: offer your recommendation. So salespeople have been taught for a very, very long time that it’s all about diagnosing the customer’s needs, understanding what they want. And the hope is that by asking good questions, the customer will figure out on their own what they really want or what they need. But what high performers know is there’s a time for asking and letting 1000 flowers bloom, and then there’s a time for telling and making a recommendation, because with too many options on the table, the customer again will get wrapped around the axle about what they should choose and they’ll fear I’m going to choose the wrong thing, and that will become an irreversible decision.

MD: The L is limiting the exploration. So in a world where customers want to continue to consume content, they always feel like they’re not enough of an expert on the technology or on the platform or on the competitive landscape or on the decision they’re being asked to make. They will consume information endlessly, and there’s no way that they could possibly develop the level of expertise that we as salespeople have. And so we’ve got to put a limit to their exploration, and the way we do that is we’ve got to earn the trust, the trust and credibility, if you will, the customers trust, and we’ve got to establish our credibility as trusted subject matter experts who have the customer’s best interests in mind, and that we can guide them through this learning journey and that they don’t need to consume all the content because we’ve already done that. And we are their trusted advisor.

MD: And then finally the T: this is about taking risk off the table. So when our customer’s hand is hovering over the contract and they’re worried: ‘boy, this is a really big investment, it’s a really big decision for our organization and what if this goes sideways on us?’ We’ve got to provide some assurance that we’ve got their back, that things are going to go fine. And sometimes it comes down to additional professional services support, not that we give it away for free, but proactively suggesting that starting smaller, getting the customer to not bite off more than you can chew, or creative contract structuring that gets us in a place where the customer feels like they’ve got a safety net if things start to slide, if they start to go sideways. So that is the JOLT Effect. And we like it because it’s memorable, but it also speaks to what’s happening here, right? It’s about jolting our customers out of their indecisive state toward action.

PH: It’s really, really interesting. And actually everything you’re talking about there, there’s a couple of words that are shining through to me, which are customer success, it’s not just ‘make the sale and that’s it.’ It’s not a new area, but it’s certainly been more in focus in the last few years that we come out the other side of the funnel with a whole new funnel, which is making sure that the product is used properly, that we keep we keep them educated, that we’re there for them. Is there an element of this in all of that?

MD: 100%. We talk about actually in that T chapter, taking risk off the table, that one of the best things that that salespeople can do is pull forward some of those customer success engagements, laying out the roadmap for how we’re going to work together, the project plan, here are the key milestones, here are the metrics. Let’s get the quarterly business review meeting set up now, let’s get all of this lined up because we know from working with companies who get a ton of value out of our solution, this is the roadmap for success. So it sends the customer the impression that you’ve done this before. You know where the pitfalls are, you know where the landmines are, you’re going to start thinking one step ahead and you’re going to make sure that we’re going to end up in a good spot — this is a huge confidence giver for the customer.

PH:  And on that note, and again, in relation to customer success, is that the area where a lot of this is about the sale and the salesperson, but when it comes to CX professionals, customer experience professionals, what are the lessons here as well?

MD: Yeah, for others who support the sales organization, whether that’s marketing, it’s customer success, I think understanding that when our customers start to waver, it is more often than not, in fact, I didn’t mention this before, but what we found is if you divvy up losses to no decision by losses to the status quo versus losses to indecision, you find that indecision actually encompasses more of those losses. 56% of the losses are because the customer is indecisive, it’s not because they’re in love with the way they do things today. And for all of us in the organization to understand the sources of that indecision so that we can work together to get our customers over the hump and get them across the finish line, again, whether that’s customer success, articulating the plan to work together, even proactively introducing you to your customer success team members, and maybe sharing roadmaps and project plans that have been successful with other clients and talking openly about the risks and the pitfalls and the landmines you want to avoid. Or it’s marketing perhaps, figuring out what are, what are the configurations that we should pre-package into, kind of, if you will, “Happy Meals,” because we know when customers buy this configuration, they’re really, really happy. So let’s package those up, let’s market around those and let’s train our sales people to actually advocate for those solutions because we know when people buy it that way or buy that configuration, they’re much more happy with the results. Or lastly, it might be finance, it might be thinking about some of those ways to do creative contract structuring, terms and conditions that provide that assurance to the customer, instead of making salespeople go and ask for permission every single time they want to grant an exception or flex a term or condition in a contract.

PH:  It feels like everything we watched and learned from Glengarry Glen Ross ‘always be closing’ is actually wrong. It’s turned on its head, Matt.

MD: Although I will say I will say Alec Baldwin did have a point. You do want to get the customer to sign on the line, which is dotted.

PH:  Just a couple of final questions, Matt. Are these same techniques that we’ve just talked about, do they apply to securing contract renewals with existing customers?

MD: Yeah, it’s a great question, Patrick. Actually, I was reminded of this recently. My co-author, Ted McKenna, who did a lot of the data analysis, reminded me that we actually did have a fair number of account managers in the sample. And so some of these behaviors about gauging indecision, offering recommendations, limiting exploration, taking risk off the table, matter as much to existing customers as they do to new customers. Now, some of those things I think might matter to different degrees. So offering recommendations, think about when the account manager is often in the position to have to not just renew the contract, but to introduce cross-sell and upsell opportunities, or ideas, new integrations, expansion. It is in many companies today ‘land and expand’ is the motion of sales. And so the account manager is the one leading the expansion charge, which is very much a sales motion. So guiding the customer, making a recommendation and also building credibility and trust by telling them what they shouldn’t buy. I know you want to go over here, but I actually don’t know that that’s the best fit for our solution. Where, you know what, in an extreme world, I know you’re looking for us to help you here. We’re honored that you turned to us, but this is actually not what we’re good at, it’s actually a competitor of ours, I know people over there, and I’d be happy to put you in touch. So these kinds of conversations can be huge credibility builders, because, again, our customer is not just going to going to feel indecision when they’re weighing the purchase, they’re going to feel indecision when they’re weighing a bigger contract next time around or renewing for a number of years, right, which is very much the job of the account manager, that indecision will creep up in any, in either scenario, I should say.

PH:  Finally, what’s made this book possible and what has allowed you to maybe turn some of the perceived wisdom around sales kind of on its head in a lot of ways is rich data, which, ironically, COVID-19, allowed you to collect.

MD: That’s right. That’s right. Yeah. I think right around the time that everyone was watching Tiger King and learning to make sourdough bread, I think what Ted and I realized was there was this golden and maybe once in a lifetime opportunity as sales researchers, which was to study sales in a truly ethnographic way, which is to go where the rubber hits the road, the actual sales conversation. And what made that possible is when the entire world of sales went virtual overnight in March or April of 2020. And so we worked with several dozen companies to, if you will, harvest 2.5 million recorded sales conversations, then use a machine learning platform to do the analysis. And so it was, again, I don’t know that we’ll ever be afforded the same opportunity, I think some sales will start to go back to live in the future, so this may be a one-time thing, but I think virtual is still going to be a big chunk of the way we sell moving forward. Customers like it, it brings some efficiencies to the sales organization, the sales person. It’s better work-life balance for our sales people and they don’t have to fly around on planes all the time, not to mention better for the environment. So it was a really exciting initiative and maybe a once in a lifetime thing, but it was this fantastic, I think, once in a lifetime opportunity for us as sales researchers to study sales in this completely new way. We were very much inspired by Neil Rackham’s work when he wrote Spin Selling, and he and his team spent 10 years physically sitting in on 35,000 sales calls and it never occurred to us that anything like that could ever be accomplished again until COVID-19 happened, and suddenly, now there we go.

PH:  Well, it’s fantastic. So where can people find more information and pre-order and buy the book?

MD: Yeah, sure. The book is coming out from Penguin Random House on September 20. The Jolt Effect: How High Performers Overcome Customer Indecision. So you can find it listed on the Penguin Random House site as well as everywhere where fine books are sold. And you can go to www.jolteffect.com and get more information there. We’ll be releasing bonus content, we have a pre-order offer out there for people who buy early, send us their receipt at preorders@jolteffect.com and we’ll sign you up for a virtual event in September that we’ll be running. And we’d love to host all of your listeners at that event.

PH:  Matt Dixon, a pleasure as always. Thanks so much for joining us on TELUS International Studios.

PH:  And a very big thanks to Matt Dixon for such a fascinating conversation. But it’s only a taste of what’s in Matt’s book, so please do check out the links we leave in the show notes here and purchase a copy for yourself. Thanks again for listening to another episode of TELUS International Studios and I hope you can join us for the next one coming soon.

Customer experience analyst and best-selling author, Matt Dixon, sits down with TELUS International Studios to share insights from his new book, The JOLT Effect: How High Performers Overcome Customer Indecision. Listen for his latest findings.

Illustration of Matt Dixon with episode title "Matt Dixon on overcoming customer indecision"

Landing page hero image - Matt Dixon

PodCast Banner - Matt Dixon

Matt Dixon on overcoming customer indecision

Intro: TELUS International Studios where customer experience meets digital transformation.

Patrick Haughey (PH): You are very welcome back to TELUS International Studios. I’m your host, Patrick Haughey, and this is a particularly exciting episode of the show because we are taking a look under the bonnet of one of the most interesting and fast growing companies in the world right now. That is Spotify. Most of us are familiar with Spotify’s platform and how the company leverages digital technologies to deliver a really strong user experience. But what about the technology that Spotify applies to make the company itself run more efficiently to automate certain tasks and processes to ensure that Spotify team members are doing only the most high value tasks possible, all of which in turn feeds into an enhanced user experience. Well, that is what I find out all about in this episode of TELUS International Studios. My guest is Sidney Madison Prescott, Spotify’s global head of intelligent automation. Sidney is such a fascinating person. The road she took to the world of technology was very different to what you might expect, and we hear all about that story. She has also had some very positive experiences with mentors throughout her career, and she explains why. And Sidney also shares her thoughts on the future of technologies like AI, machine learning, automation, quantum computing and lots more. If you have been following the series so far, and like what you hear, please hit follow on Spotify or subscribe on Apple Podcasts and leave a rating or review. So let’s meet our guest.

PH: Sidney Madison Prescott, Global Head of Intelligent Automation at Spotify Welcome to TELUS International Studios.

Sidney Madison Prescott (SMP): Thank you. I am excited to be here today.

PH: I’m looking forward to hearing all about how you got into technology, and I know you’re an incredibly passionate advocate for technology, but I know it wasn’t what you started at, and I want to find out how you got into technology from where you started. But first of all, let’s just start off where you are today. I’m fascinated by your title, as I’m sure many people are. What does the global head of intelligent automation at Spotify do?

SMP: Great question. So I am leading a team of engineers and also solution architects on a global scale to build out an intelligent automation footprint at Spotify. And what that entails is looking at several different technologies. So we leverage robotic process automation, machine learning and artificial intelligence in order to build efficiencies into the - all of the different business processes that we do today within Spotify. And so my team sits within the financial engineering organization, but we have a reach to all of the different business teams at Spotify, and we’re focused on looking at what are all of the very manual, repetitive, tedious tasks that we do as Spotify-ers and how can we automate those tasks to drive greater efficiency, greater data quality and really ensure that our employees can focus on more value added task at the end of the day as a whole around the organization?

PH: Ok, so this is basically streamlining and being very smart about how Spotify is run as an organization as opposed to anything to do with the platform itself that we would pick up and use.

SMP: Absolutely. So it is from an organizational standpoint, how do we streamline and make the, I’ll say, the back end of the work that we do as efficient as possible, but in that we are also enabling faster time to market and things of that nature which do come out on the application side.

PH: Absolutely. Maybe to just sort of illustrate everything that you just said there, is there an example you could give us about your job at work? Is there something - Is there something that people were doing in Spotify that you recognise that there was an opportunity for automation here, giving them higher value tasks in that case. Do you have an example?

SMP: I do, yes. So we are working today as a team with our ad operations employees. And what we’re really looking at is how can we take the task that the team does today and how can we make those more efficient? One example is when we go into the Spotify application and we look at all of our different audio ads that run within the application, we have to test those ads to ensure that they - the integrity, the audio integrity is there. And so this is a process where we take each ad and we test to make sure the audio, the visual that everything is up to spec for that particular advertisement. This is a manual process, but we have been able to automate this process and leverage robots to actually check each advertisement to make sure that it’s running properly, that it is showing the right or the correct specs in terms of the visuals and that the audio levels are appropriate. So this is a really perfect example of something that you wouldn’t think that humans are doing today, but in reality, it’s a very integral part of the responsibilities of the team.

PH: Yeah, very interesting. And it must be hugely fulfilling to be able to take a sort of a wide view of everything that everybody in Spotify is doing and spot the opportunities to actually make it smarter I guess.

SMP: It is. It’s really fascinating to weave together all of the different business processes that really make up how we do work at Spotify and how we deliver on our product. And so one of the greatest aspects of this role is getting a high level overview of all of the different business units, their responsibilities and how those are interconnected and then taking a look at ways that we can optimise the processes of those teams, both from an upstream level and also downstream to really make again efficiency the key, I would say, value proposition of the deliverables for my team.

PH: Ok. In a couple of moments, I’d like to dive a little bit more into some of the technology that you use so the technology at play in your role because it’s so fascinating. But first of all, tell me how you got into technology. I know you didn’t start in tech and I think, am I right, it was an internship that changed everything for you.

SMP: It did, yes. So I started out as a philosophy major when I was in college and I was looking to go to law school and I happened to have a very fortuitous moment where one of my peers and in university pointed out to me an opportunity for an internship. And that is kind of, I would say, where the tide turned. I took an internship within configuration and asset management, and I quickly was fascinated by all of the different nuances of the role and what it means to work as a technologist on a global scale. And within that role, it was a really wonderful learning experience because I was able to help facilitate work for different teams and really again understand how those teams work together at an enterprise level to really produce deliverables. And that is where I really fell in love with technology and also with really the processes that we do to really innovate and redefine how we can deliver value at a firm level.

PH: So also in that internship in that firm, were there certain types of techs or at play with certain platforms that were being used to achieve the goals?

SMP: Yes. So I was working specifically with disparate databases and really looking at what is the integrity of the data within these specific databases. And then more importantly, how are these databases communicating with one another? And can we trust that the way that the data is extracted, transformed, loaded, can we trust that that is accurate, that it’s timely? And so one of the things facilitating this work that I quickly began to realise is that we had a lot of systems that were supposed to be integrated together and it was assumed that all of the timing of those aforementioned aspects were correct and they really were not. So we went about a really, first a fact finding mission and then really from understanding the attributes that we should have been collecting within those different systems and understanding the ways that the timing was off. We then started to think through, OK, how do we really facilitate a better connection? How do we facilitate better integrations between these different systems? And so that was really interesting to me because it taught me a lot about the assumptions that we have as technologists about pre-existing systems or systems that are part of the enterprise before we particularly work for a company. And it also taught me a lot about change management and about really thinking through how you can bring others along on this kind of journey of digital transformation within a firm.

PH: And I know one of your mentors through your career. I think you pointed out in saying that he taught you how to tell a compelling story about your team’s work, and we might come back to them a few minutes because I think no matter what job industry role you were in being able to tell a compelling story about what you were doing, what your team is doing is such a valuable quality. So we’ll come back to that in a couple of moments time. So from that internship, then you had sort of found your path. So where did you go from there?

SMP: So from there, I worked really focusing on data quality and the integrity of data, and it gave me a passion that I still have today in relation to data visualizations. How do we create data that will be a valuable asset to our business stakeholders as technologists? And fundamentally reminding ourselves that at the end of the day, we really need to be able to have tangible evidence of the value that we’re creating with all of our different automated solutions. And so as I honed that perspective within data quality and governance, I had an opportunity to then complete a proof of concept on a very new technology, which was robotic process automation. And that is where I began to get into intelligent automation. So through running that proof of concept, I learned about robotic process automation, I began to learn about all of the different tools that make up intelligent automation as an industry. And I also specked out the tools that existed already around the world in relation to driving efficiencies, driving productivity within teams. And that really led me into my current role, really standing up and scaling out and maturing intelligent automation centres of excellence.

PH: Well, one of the words that come up and really define what you’ve done is this word intelligence and intelligent automation. How do you define intelligence? What does it mean in this context, in your own view?

SMP: Great question. So there are a lot of different definitions for intelligence. From my perspective, in terms of the team that we have today and the technology that we are leveraging, we really are looking at the distinction between: is a particular automation cognitive, in that it can facilitate different ways of learning quote-unquote? And is it able to recognise different characters? Does it have spatial recognition, things of that nature. Now there’s a separate part of the intelligent automation piece, which is also the robotic process automation. And those robots are not cognitive. Meaning that they cannot execute anything that has not been predefined in their developer build workflows, and so where intelligent automation really comes together is we start to think about the robots that can only execute on their predefined workflows and combining those with artificial intelligence or with machine learning engines and that combination of tool sets and different ways, ways of basically computing. That is how we get to the intelligent automation piece. So it really is the amalgamation of these different tools coming together to be able to facilitate a specific set of business outcomes, which we would typically relegate to, let’s say, human intelligence rather than a machine.

PH: Well, one of the questions that I know it kind of comes up and when we talk with this field is when it comes to machine learning algorithms, are they really learning or are they just memorizing? And I guess, can we tell the difference between the two, really?

SMP: I think that’s a great question. So if we think about it, it really comes down to how you really break out the different categories of kind of machine learning, deep learning, and artificial intelligence. So if you think about machine learning, it really is a subset of artificial intelligence. And so it’s basically creating systems that can have the ability to learn and improve over time with experience. Now, machine learning models need a large amount of data very, very much like the human brain. We need a lot of data continuously over a lifetime in order to build up our understanding of the nuances of, say, a chair or the concept of education, the concept of computers. And so machines are very much the same. We are able to basically build up their understanding of a particular concept through the amount of data and really also curating the ability for the machine to curate that data is very important. I think one of the other things I would say is in terms of learning versus memorization. I believe it’s a bit of both. And we do this as humans as well whereby we learn quite often by memorizing. And it’s very interesting, even if we think that we aren’t memorizing something, we are. So, for example, memorizing where a particular Starbucks is located on your corner or, you know, memorizing the way to get to a specific location - that is a form of learning. And I believe that machine learning can basically facilitate the same levels of understanding, whereby it’s a component of a little bit of memorization, but that memorization actually enables the machine to then learn different patterns, learn different potential outcomes that will help to solve problems. And so the last part of that is when we start moving into another subset of machine learning, which is really your deep learning. And that’s really where we are attempting to create a very similar computer network that mimics the neural networks of humans. And so that deep learning, this is where we get into the potential ability to delve deeper into a little bit less memorization and a little bit more learning of patterns again from a wide variety of data that is fed into that particular neural learning network.

PH: It’s such a fascinating area, and I know I said a few minutes ago, you kind of you’re now very far from where you started out, but hearing you speak there - I do get the whole philosophy major thing because this the type of thinking, the structure of thinking, I would guess, is quite similar. There’s patterns there.

SMP: There are, yes. One of the most fascinating things that I found out as I moved from being a philosopher and I would still consider myself a philosopher, but a philosopher slash technologist is really the focus on logic. It’s very, very fascinating. So the logic aspect is extremely similar between the humanities and technology, specifically with the logic that we actually use to code. So we use if then statements, which is something that philosophers base a lot of their logic and argumentation off of. So there’s a lot of similarities between the fields. And I think that is also why we have a lot of ethicists and philosophers that are moving closer into the world of technology.

PH: Yeah, absolutely. I guess they were the original technologists to in some ways, I guess way back when. I got a couple of questions in from the team who know a lot more about this stuff than I do, and I think you’re going to appreciate some of the questions. So first one is; Most AI applications to date have focused on software products like image recognition or targeting advertising or content evaluation, and for that reason, AI’s presence in the physical world remains limited. That being said, how far are we from being able to really change the way people do things such as self-driving cars, robots, construction, etc.?

SMP: That’s a great question. I believe that we are still - I think that we’re making strides, but I think that we are still a ways off and that is primarily because of the challenge that we face as humans when we start to attempt to build something in our image, so to speak. And we have this inherent problem, which is; we are limited by the fact that we don’t know what we don’t know, which is a kind of a logical conundrum, even when we think about the way that today human beings understand the brain, right? How it works. We do understand it to some extent. But when you talk to neurologists, you talk to doctors. You quite often will hear a disclaimer that you know, we don’t really - we aren’t exactly sure why, you know, x y z works like this. So we have an understanding, but we are very aware of the things that we currently don’t know or we aren’t sure of, but we do not have visibility into understanding what we don’t - that we don’t know what we don’t actually know. And that makes sense. And when we start to think about that, that does start to define how we build out these self-driving cars, how we build out autonomous robots. I believe as we continue to evolve our knowledge level of understanding that we have, specifically about human neurological capabilities. And doing that through scientific research evaluation, I believe that that research will fundamentally benefit the innovations on the technology side. So I think that challenge is present where as our knowledge builds, we then build that into how we conceptualise these different tools. But it’s still, it’s ever growing. And the progress that we’re going to make is that it’s always going to be slightly offset by that. Those additional layers of understanding that we just don’t have in relation to human cognition and how we can actually build a computer system that in essence mimics human aptitude for learning and adapting in a given environment.

PH: Yeah, it’s such a fascinating time. Another question is it a problem that the largest players in AI are primarily software and advertising companies, rather than companies that manufacture things? Or are these tasks inherently harder?

SMP: No, I do not believe it’s a problem. I actually believe we need synergy between both those kinds of, I’ll say, software companies and the manufacturing firms. I believe that synergy is what’s going to allow us to achieve the next iteration of artificial intelligence improvements. And when we think about it, it’s been quite a conversation. I would say over the last few years about the importance of every company being at the forefront of technology, and almost every company must be a technology company if they hope to remain an industry leader in their given area. And so part of that, I think, is whether it’s a software company, whether it’s a manufacturing company, how do we actually bring those two together because they’re both sides of a different coin? They are both attempting to solve complex business problems through the use of different innovative technologies. And so I believe it’s less of a question of which tasks are harder, whether it’s software or manufacturing and more of a question of what is the best combination of the two that can help us successfully remediate business problems.

PH: Yeah, that’s a really good answer, actually. What work is being done to ensure that AI is more inclusive of things like different accents and dialects and cultures?

SMP: There is a lot of work that’s being done on a technological feasibility and execution standpoint. But I believe that there is a fundamental change outside of that enablement that we need to do, and that is really continuing to drive the diversification in this particular area of technology. When we drive diversity in technology, so diversity of age, ethnicity, race, gender, sexual orientation, et cetera, having those voices and those experiences from that diverse set of engineers in the room when the decisions are being made as to what is going to be, let’s say, the default language for a particular application or the default, maybe graphics skin tone setting for a particular application. Having a diverse set of engineers in that conversation is the way I truly believe we can ensure that all demographics are included. So by putting a diverse cohort of individuals into the design process, the software development lifecycle, we can help better enable that inclusivity that we are looking for in terms of the ways that we design out these artificial intelligent systems.

PH: Yeah, just throughout your own - you know, we started kind of by talking about, you’re here today because of an internship, really, that was your sort of, the moment that brought you down this path. And of course, with internships comes mentorship. What impact has mentorship had on your career and I guess particularly as a woman in tech?

SMP: This is a question that I’m asked a lot, and I love this question because mentorship, I believe, has given me such a great understanding of the unspoken nuances of the corporate world. And then even more specifically, the unspoken nuances of the technology sector. And so making the transition from a university and more academically focused career over to technology and senior leadership. I did not have that understanding, that built up understanding of those unspoken nuances of how to navigate the space and to your point, specifically as a woman, as a woman of color. And so mentors, my mentors really helped me, I would say fast track my understanding of all of the smaller but extremely valuable points of reference that I did not have as a, you know, someone new in their career, just starting out in a particular industry. And also, that mentorship helped me to build up my confidence, which I think is absolutely essential as a woman in technology, having a level of confidence about not only the knowledge, but also your ability to think critically about different scenarios, whether it’s from a leadership aspect or development aspect, I think is absolutely critical to success and to the ability to retain not only employment, but also to move up the corporate ladder to move into the C-suite. So I think that a focus on having a mentor really does help you from a confidence perspective. It’s helped me quite often in my career to have my mentors as a sounding board about different business challenges that I was facing, or even just management challenges that I was facing in relation to being a people manager within the technology sector, which is a very nuanced area to be in. So I believe that mentorship helps us in so many different ways, particularly if you are within an underrepresented demographic within the technology sector.

PH: And are you a mentor to anyone or, in the future, is it important to you to become somebody’s mentor?

SMP: Oh, yes, absolutely. So I have, I’ve been a mentor to several new, I would say, young professionals who are just starting out in the technology sector and it is something I’m very passionate about because I do - I would say quite a bit of my success is built on that foundation of the fact that I was a mentee as I moved through my career. So yes, I do mentor and I do plan on continuing to mentor and continuing to speak about the relevance of mentorship specifically for women in STEM fields.

PH: The way you speak about mentorship and your team, etc. I think, you know, you come across like a great team leader and one of those things about being a great team leader is being able to, as we mentioned earlier, tell a compelling story about the work that your team is doing. So, any tips for us? It’s a great skill to have.

SMP: Yes. So telling a compelling story is also, I believe, a key to the success that I’ve had thus far in my career. And it really starts with clearly defining the business problem you are trying to solve. Clearly defining the stakeholders that are that will be involved will be key players in the way that you actually transition a particular problem into a solution. And then also really identifying what are the ways that we can define success. And these should be tangible metrics that you can measure and that you can present to your senior leaders, to your executive sponsorship in relation to the work that your team is doing. So a lot of the time I find as technologists, we put our heads down and we come up with an incredible solution and quite often it’s lost in translation the value that that solution provides back to the business, so it’s very important to define out the ways that you can communicate what the value your team is delivering and also really to find out how you can better serve your stakeholders. This is a big piece as well, bringing the stakeholder along on the journey rather than having kind of heads down and so focused on the technological solution, building that empathy for your business stakeholder in relation to the pain point that you are attempting to automate - that goes a long way also in building that compelling story because your stakeholder then has a key, you have their buy in and they become really an advocate for the work that you and your team are doing.

Spotify and the future of intelligent automation

Subscribe and listen:

Share

Be the first to know

Related insights

Processing vast amounts of Salesforce call data with intelligent automation solutions

What happens to humans after we automate?

Enabling a global transportation giant to achieve its hyperautomation goals