[00:00:00] Phil: turning unstructured data about voice of customer into actual action, like closing that loop, 

[00:00:06] Aditi: This is where, you know, I'm thinking of technology and agents, right? Like a voice of agent can pick it up via call transcript, and then you extract, the metadata, so Topics, intent, segment. And then, you post it in Slack and then say, well, three recent calls flagged manufacturing buyers asking about, competitor versus our differentiation.

[00:00:28] we recommend, reviewing current messaging, right? that gets assigned to a product marketing manager and then it suggests maybe a messaging tweak 

[00:00:35] And then you track the action, right? Like heard, routed, resolved, and, and measured. This is a workflow that we can easily automate. 

[00:00:43] 


[00:00:46] In this Episode
---

[00:00:46] Phil: What's up everyone? Today we have the pleasure of sitting down with Addie Al, vice President, digital Marketing and Demand Generation at Teradata. In this episode, we explore underrated channels where you can capture customer insights, MarTech tools that can help with [00:01:00] activating voice of customer, how to use rapid response teams and marketing ops, and how to balance quantitative data with customer conversations.

[00:01:08] All that and a bunch more stuff after a super quick word from one of our awesome partners.

[00:01:11] 

[00:02:17] Phil: Addie, thank you so much for joining the show. I really appreciate your time.

[00:02:21] Aditi: Thanks, Phil. I'm a huge fan of your podcast and that's why, as you know, I reached out saying, can I be part of, of this Awesome, awesome, um, you know, ecosystem that you have. So, very excited to be here.

[00:02:35] Phil: I appreciate you saying that. Um, yeah, a lot of folks kind of listened to the show, curious about jumping on and, uh, when you reached out, looked at your background, you sent a bunch of stuff that you had written about and, uh, we're sharing in different, like conference speaking tours. And so I was like, yeah, there's, there's a lot of stuff that we can chat about here.

[00:02:54] One of the things that you had suggested was this topic of how to capture, [00:03:00] activate and, and make more of the voice of customer that you have, uh, kind of data points in inside your company. So I'm excited to chat about that. Um, let's dive right in. So like, marketers are super busy, right? Like we have a ton of directional data that tells us.

[00:03:16] What's working, what's not working? What should we do next? We've got surveys, analytics, ai, endless dashboards. Uh, a lot of folks like to make fun of dashboards and how many dashboards marketers have. There's also plenty of other departments who think they know marketing and, and they can do marketing.


[00:03:32] 1. How to Use Customer Conversations to Validate Marketing Data
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[00:03:32] Phil: You've highlighted that we're missing something by not talking to customers as much in person anymore. How can we like bridge that gap combining old school customer empathy with a lot of the new practices with digital marketing, like analysis by paralysis we're kinda dealing with today. Um, do you think that we're getting too enamored by like the promise of MarTech and, and all the insights and sometimes, you know, simple conversations with humans?

[00:03:58] Uh, our customers work a lot better. Give [00:04:00] some practical examples there and, and tactics that we should be thinking about.

[00:04:04] Aditi: Yeah, I mean, I think, um, you know, I come from the old school, uh, model Phil, where we used to go, you know, to the market and talk to people, um, talk to our, our customers, and those can be, could be anyone, right? Like selling retailers and, you know, truck drivers and mechanics. Um, and. While, um, you know, it, it, it was laborious because you had to take down notes, but, and, um, you know, and then you had to think about, okay, where are the trends and how do you really synthesize it into that one insight that you're, you're looking for?

[00:04:41] I thought, I think that now, you know, 10, 15 years later, um, now that we have all this technology and spiting out these insights, it makes you, the, the validation piece is missing, um, in my [00:05:00] view. Because if you get an insight that says, well, you know, talk to your customers about x, about, about this, because this is their pain point, I would love to see, or like, it, it would be so helpful, you know, to actually listen to a customer saying it, because a lot of times.

[00:05:21] They use words, um, you know, that are, that are so much, you know, resonating with them versus, you know, with marketers where we are probably relying on our own, own fancy words and buzzwords, um, so to speak. And, you know, more thinking, oh, this will resonate with our customer. But I think that this would just make our, in, in a lot of ways, make our jobs even more easy because you have been able to hear what your customers have been talking about, you know, through transcripts or just going and sitting in a meeting.

[00:05:54] And you, you don't need to have hundreds of those, right? You just have five of those [00:06:00] and you will just come out, come up so much more confident on the data that you are seeing, the insights that you are seeing, you know, that trust that you, you'll trust it more because you have gone to the source of of truth.

[00:06:13] Um, so for me, I think that that's. One thing, which, um, a lot of, a lot of marketers, including myself, um, you know, have forgotten, um, or like sometimes miss out on. Um, and I think that that's something which all marketers need to do. I think in B2C they still do, there are way ways that where you get to hear, um, you know, your customer talking about it.

[00:06:39] And it's also just the nature of, uh, the B2C marketing, the type of channels that you have, the messaging that you put in, that you have to be a lot more closer. B2B should be doing that a lot more. Um, you know, because we just think, oh, it's a data scientist who wants to, you know, or who love this [00:07:00] product. go talk to a data scientist. Like there are students who are aspiring data scientists who have been using a lot of the software that all these companies have, and they will be potential, you know, users, potential decision makers, the amount of, and, you know, it's free. Not very expensive, but the insights that you can get, those can be corps that, you know, you can use, you can deploy rather than, you know, paying in a, a creative or a, or a content agency to create all that content.

[00:07:31] So it has to be a mix. I'm not, I, I'm not saying that we, we, you know, we don't use technology just because there is now so much data, which you have to. You have to know and learn, but you need to also determine like, what, where do you need, like, what are you using those insights for? Um, right. Like, not everything has to be as complex.

[00:07:54] Not everything has to be, um, you know, as dependent on a model running and then [00:08:00] figuring out the confidence, um, you know, uh, of, of the, the model or the results that we are seeing. It, it needs to be very much aligned to what, where do you want to use this insight for, in, at what stage? Like what stage? But it's important that we do that.

[00:08:18] It's, it's important that we incorporate as a marketer in everything that we do, every aspect of our life. It's not just. When you need to design a campaign or when you are thinking about what you know, your product, um, fit should be, or a roadmap, it needs to be done by every, at, at every single step. But again, needs to vary at what level of insight do you, um, you know, you, you really need.

[00:08:43] So that's what I would say, um, is depending upon the need, um, or where you needed an insight, um, the question always should start with why do we need to do this? What, what does a customer need? And then you find out how you get that [00:09:00] information. Do you use technology and all the bazillion dashboards to the answer that you want?

[00:09:06] Or do you just go and talk to five of your most loyal customers, most active customers, um, and then, you know, determine how that works. And the best thing about this is you can always keep on optimizing. Um, you know, it's not that you got something and then you have to make sure it's a hundred percent there because that's the.

[00:09:25] Nature of the game, you always need to keep on changing. You need to keep on adapting.

[00:09:30] Phil: Yeah. Such a great answer. I love your point about it's not just like one point of data, like one of the main objectives, uh, objectives or not objectives, um, objections that I've had with people that are in the marketing seat that are being asked, like spend more time chatting with customers. It's like, it's easier said than done.

[00:09:50] Like I've got a ton of stuff on my plate and like reaching out to people, offering them something in exchange for like, sitting down with us for 20, 20, 30 minutes. 'cause like these people are busy too. Our [00:10:00] customers are busy too. And the thing that a lot of these folks struggle with is. Is, I've got a ton of data telling me what my customers like and what they don't like.

[00:10:09] We launched 15 campaigns last year. Some performed well, some didn't. There's a lot of quantitative data that there, there's a lot of signals in, in that data. Right? 


[00:10:19] 2. Balancing Quantitative Data with Customer Conversations
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[00:10:19] Phil: And if I chat with five customers next week, those are really good qualitative data sources and insights that I can get from it. But it's five people.

[00:10:27] Like how meaningful and representative is, are those five conversations when I have all of this quantitative data to work with. So they, marketers are often like fighting those two battles. Like the, I think you're, the, the talking to customers is a bit more old school, like the, the focus group idea, chatting with humans versus like, now we have all this data, all these signals.

[00:10:49] So what are your thoughts there on like the, the quant versus qualitative arguments of like a voice of customer.

[00:10:58] Aditi: The, where I would [00:11:00] start with is when we didn't have automation and technology, and I'm probably going 15 years back when digital was taking, taking off, and I, I am talking my days, you know, in, in working in India, my, my career starting in India, US probably adopted this or had this revolution sooner. Um, but we did a pretty good job, uh, with the, the limited, you know, data that we had and marketers did a pretty good job with the, with the data that we, we had, um, in terms of talking to the, to, to consumers, talking to customers and whoever you can find.

[00:11:38] And then there was the limited sales data or whatever, you know, in Excel sheets we had at that time, which we were running pivot tables. Um, well, I think the, the, the pro the problem right now, or why it's becoming more complex is because we are not thinking is why do we [00:12:00] need data? Why do we need customer insights?

[00:12:04] Like, what am I solving for? Because a, right now it's you. Anything that comes to your mind and you're like, oh, let's get, let's get data. Let's use a, a technology to give us answers. But back, you know, it how your, your brain or your your brain has been, has been trained or the work that someone needs to do that le that level of deep work that a marketer needs to do.

[00:12:29] You know, thinking about, okay, I'm doing market sizing. Why am I doing market sizing? Um, what is it that I, I'm trying to do? I'm trying to launch a new product. What is, what are the type of information that I need to answer? So there, there is this whole road, like a plan that you have to, you have to create.

[00:12:48] And as you go through that stages by stages, you, you know, what the guardrails should be. Um, you know, right? Like, okay, here is where I need maybe the market, you know, I need the market sizing data and maybe the market [00:13:00] research data. There is no need right now for us to see, okay, what keywords are, are people searching for?

[00:13:06] Or, you know, whatever. Again, the data that, all that data that's available. So the, the, the problem, or maybe the way for us to solve for it is really breaking down your problem into solvable, you know, parts, and then looking at it as, as a shell and saying, okay, for me to solve this, what information do I need?

[00:13:29] What are my guardrails? Because then you will, you will get your answer as to what data you need, what you know, whether it's a secondary data, it's primary, you know, research data or it's just what you know. We have, um, available third party data. What is it that I need to use and at what point this should be enough for me to move to that next stage of solving the puzzle.

[00:13:51] And I think that that's, that's the difference is how your, how a marketer thinks about solving a, a [00:14:00] problem. And so it should never start with, I have all these data sources and I have, you know, I can go talk to customers, et cetera as well. But it needs to start with what's the bigger problem that you are solving?

[00:14:12] And then you determine breaking it into smaller pieces and then saying, okay, now what data will help me get to an answer? So. I think that that's how I would like, I think about it as well, because I sometimes get overwhelmed by all, uh, you know, that we have, and all the suggestions that people have is like, wait, use this data.

[00:14:33] We can use this, you know, sprinkler dashboard and the, the, the, the keyword dashboard that we have and all the benchmarking data, and it has to go back and say, but why do we need this? Is it the right time to look at this data? Um, and that's again, going back to a lot of times we think, or we have started thinking that technology is the solution.

[00:14:56] Technology will give us answers, we forget. Technology is [00:15:00] just an enabler. You know, it's whether you go talk to people, whether you run it and pivot like in Excel sheets, like, or you have a, a, a, you know, a great, a predictive analytics dashboard that tells you what stage your, you know, customers are in, in the buying journey.

[00:15:17] So. That's how I, I look at really solving for this immense amount of data. Um, you know, that you have, it's, you have to go back to first principles. Um, I, I think that should help you a lot.

[00:15:32] Phil: What is a use case? What, what are we trying to do with this? And I, I think like, practically speaking, maybe let's say we've got a use case that we pick, maybe it's retention, activation, whatever. Um, but practically speaking, like 


[00:15:44] 3. Gathering Customer Insights From Underrated Feedback Channels
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[00:15:44] Phil: what are the most effective ways you think are to capture voice of customer today or evidence of customer?

[00:15:50] Everyone does, you know, surveys, collection surveys after they buy or after they like land on the website and they fill out a form. There's NPS surveys that a lot of customer [00:16:00] success teams do. Where should we be listening specifically, like as marketing teams? Is it sales call recordings? Is it support tickets, social media, um, you know, user communities.

[00:16:12] There's all these different sources. Once we have picked one of those use cases, are there like any underrated feedback channels or clever tactics that you've used to gather insights that, that others might be missing? Um, curious your thoughts there.

[00:16:29] Aditi: I. A lot of times, and you have to think about who your customer is, who you're going after. Now for, and I'm talking from a, for a B2B lens, we are selling to a buying group, a buying committee, right? Everyone has different roles in that someone is a user, there's an influencer there, there is a, there is a decision maker.

[00:16:52] Um, it depends on who, what you're, what, what, what you're learning, who you are looking to learn from. Um, I think [00:17:00] again, if you're looking to engage with users, people who are, you know, using your product or who should be using your product, um, you, them using your product. So in product analytics, I think, um, you know, or like, or product, um, you know, surveys that you get while you're using a product where you know, you're saying, I like this, or I don't like this, or I need more information.

[00:17:24] Great, great avenues for, for us to, you know, get some insights because it's, while they're using the product. I think that, and that just gives you, and there are different ways you can get feedback, right? Like heat maps and them themselves, like they're sharing feedback, um, through a, a survey or, you know, saying, I like it or what, whatever, you know, or even the journey that they're taking.

[00:17:48] Um, communities I think are becoming, um, this, this really, um, upcoming, I want to say channel where you, we, we should learn to get there and [00:18:00] get more insights on what people are talking about. Um, you know, at at, um, at Reddit, um, you know, and all these community forums, um, that you have. Um, I think the other piece, which, um, a lot of companies have started doing and, and I don't know how much they do, but you have that option of recording is.

[00:18:20] Sales recording. Um, you know, and especially it's also the M-D-R-I-S-R calls that you have because it's, again, very much layered, right? You're, it's a, it's a, it's a long selling process. It's like the first time that you are getting in touch of a customer or like a, a potential prospect. And so while you've been doing all this, you know, digital marketing, which you are seeing, and, and you, you get finally a, a, a leader or that person.

[00:18:49] When you speak with them and when you hear what their needs are or like what they're looking to understand, it gives you insights. Phil, like just recently we got an insight, [00:19:00] which just made us change our overall approach to how we were planning to engage, um, with these, with these prospects. Because they were like, I thought you guys are selling, you know, this point in time solution.

[00:19:13] Um, and, but looks like that's not who you are, but that's what you've been, you know, telling me. And I am very much intrigued by it. And, you know, and that's, and that's just, you know, from a few, um, you know, um, recordings that we, we could, um, gather and we inferred and then we quickly switched, you know, our approach.

[00:19:34] Um, and then I think the, the final thing which, um, which companies are doing, um, and maybe need to do more is events. You know, your third party, like events that you sponsor, your third party events, wherever it is, physical, uh, virtual, great way to get intel from, you know, people, uh, who are [00:20:00] at the event, right?

[00:20:00] As part of, of networking, and again, now these are for, for companies who invest in this type of a channel, but I know every, every sales person likes to attend events every. Everyone, you know, likes to be in a certain place, um, and, and talk to people. So how we can really use all these insights that they, they get, um, they can.

[00:20:23] Um, and then we use that from our end, I think is another, um, great way. In fact, we had to solve for how do we automate it because this was just so much insights we were, we were getting. So it was not really about, you know, did we get any, uh, it was, you know, beyond did we get any lead from an event, right?

[00:20:40] Like, are we getting the ROI, but the secondary, um, objective of us being, there was all this great information that we were getting and companies just need to, to use that, um, a lot. So I don't know if I, uh, answered your question of the few underrated, um, channels, but I, I think that these are the ar areas where [00:21:00] we are seeing a lot, um, that we are benefiting from beyond the, you know, general NPS, um, win loss analysis, anything.

[00:21:11] A lot more, you know, dynamic, more, more real time where the person is in, is in actual, you know, right. A mode. Um, without knowing that they're providing feedback, because then it just changes the whole game in my view.

[00:21:25] Phil: Yeah. Yeah. So true. Lots of good sources there. So what,


[00:21:30] 4. Activating Voice of Customer with AI Agents
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[00:21:30] Phil: let's chat about, like some of your thoughts about activating some of that data, like turning unstructured data about voice of customer into actual action, like closing that loop, if you will. I know AI is perfect use case for making sense and, and, and figuring out ways of automating, um, unstructured data that, that we get from some of these conversations, uh, at events or some of them are recording, right?

[00:21:55] Um, you know, things like auto tagging themes and extracting [00:22:00] customer quotes from call transcripts. A lot of people love use GA using gong for, for sales calls. And you can like push those insights into Slack. Certain team members are updating persona docs that you have. Maybe they live inside GPT or updating, onboarding flows also, or customer emails feeding that into.

[00:22:19] The data science models that you have for propensity models and, and, you know, processing all of that data. What, what other ideas come to mind? Like, how can we automate the component of, all right, we have a use case that we picked, we have a bunch of data points that are unstructured. How do we put that into action?

[00:22:38] What are your thoughts there?

[00:22:40] Aditi: So I think you, you have to, so here, here is the interesting thing, um, and we probably should talk about it because I'm looking a lot into AI and how do I use, you know, AI agents as an example to, to. Automate the voice of, of customer, um, [00:23:00] right. And it's not just in marketing, but I would say across all the business functions, because everyone is getting, um, customer feedback.

[00:23:08] Um, I think it, it starts with, so you have to think about like, what's the function that you, that we are, we are trying to automate? Um, is it capturing and tagging, um, routing, tracking summarization and activation, right? So it's like you have to, I think about, if I were to think of what would be a stack, right, that you have to, you have to build and what would be the function of it.

[00:23:31] So, um, it's like, and, and there are multiple tools that you do that, but I think of it as in terms of, well, um, you know, a gong call reveals a trend. Um, you know, multiple buyers from manufacturing as an example are asking, how do you. Compare, um, to this competitor on ai, you know, um, using AI for manufacturing efficiencies.

[00:23:57] So, um, you know, the, a voice, and [00:24:00] this is where, um, you know, I'm thinking of technology and agents, right? Like a voice of agent can pick it up via call transcript, and then you extract, um, you know, they extract well, okay, what's the intent? Are they evaluating or are they just, you know, answering, you know, looking for awa like awareness?

[00:24:17] What's the segment, right? Industry is manufacturing, um, you know, what's the topic? And again, the tagging thing, you, that's where you're talking about, right? But what are those? Tags or the metadata, so to speak, right? Topics, intent, um, segment. And then, you know, you, you post it in Slack and then say, well, three recent calls flagged manufacturing buyers asking about, um, you know, competitor versus our differentiation.

[00:24:44] Um, you know, we recommend, uh, recommend reviewing current messaging, right? As just as an example. And then that gets an, that gets assigned to a product marketing manager and a campaign owner, right? And then, um, you, and then it suggests maybe a messaging tweak and a one [00:25:00] pager update based on what it is.

[00:25:02] And then you track the action, you know, in, in a dashboard, right? Like heard, routed, resolved, and, and measured. So I mean, I think that that's where, um, you know, you, you and I know all these steps require, okay, what are those tools, uh, that you, that you use, and then how it really gets integrated into, into that workflow. This is a workflow that we can easily automate. Um, Phil, um, doesn't have to be manual anymore. Um, the tech probably today auto can automate 70, 80% of the process. And of course with humans in the loop for judgment and, and, you know, prioritization. But, um, I think that this is in fact, um, one of the, one of the, um, maybe underutilized use cases, um, you know, for companies to really see how we unlock the value, um, of, of VOC, um, through [00:26:00] automation, because it's not just marketing, um, it's everywhere.

[00:26:03] Uh, product gets a lot of. Um, you know, customer, um, data points, um, operations like cust, uh, GTM gets a lot of data points. Um, um, you know, HR gets a lot of data points as well. Um, you know, internal as well as external finance gets a lot of data points around stakeholders, investors, all that. So how can you know this is that ideal?

[00:26:28] I would say, scenario where there are these silos existing and then how can you use this technology or, or automation to unlock value? Um, so it's, for me is, is a very exciting, um, you know, use case, um, for us to, to automate and, and get some true value without spending a lot of money. 

[00:26:48] 

[00:27:33] 

[00:28:27] ​


[00:28:32] 4.2 Voice of Customer Martech Examples
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[00:28:32] Phil: can you think of like one example, the, the first example that comes to mind to, to walk us through like one of these automations, maybe something you've built in, in real life or, let's say, um, your account team was having a conversation with.

[00:28:45] A deal that was lost and that's recorded on Gong. And there's a lot of keywords and certain objections that came out of the reasons why certain person decided not to purchase. And you're automating that [00:29:00] those keywords, like those, those insights or the voice of customer and it's going to Slack and that's being sent to the team that's building like personas.

[00:29:08] And so they're tweaking the persona here because of the, the data that's coming out of that. Like, something more about like getting end points about the voice of customer and then like throwing that into certain places. Um, I don't know, like one of the ones that like comes to mind, um, they're, they're friends of the show, uh, the company called User Evidence.

[00:29:27] I dunno if you've heard of them. Um, they're a startup and they're basically like, um, I think they call it like a user, uh, customer evidence, but essentially, um. The category of tool that like helps with the voice of customer for testimonials specifically. Like there's a lot of data in existing customers that have a testimonial to share.

[00:29:47] And so user evidence, like they basically built a product that lets teams capture product feedback, um, through surveys and like review sites on G two and stuff like that. And then they automatically surface the [00:30:00] best quotes from your existing customers and testimonials and it turns that into like on-brand marketing assets that are ready 

[00:30:06] Aditi: Not help.

[00:30:07] Phil: on like social channels.

[00:30:09] You can put 'em on the website. They can be pushed to like other tools in your stack. Are there like other use cases like that or tools that come to mind?

[00:30:16] Aditi: Oh yeah. Got it. we actually, uh, you have been using, uh, bright Edge, um, and their Bright Edge is the, um, you know, SEO platform, uh, their AI tool, which basically, um, is helping us automate content briefings, um, which was earlier.

[00:30:35] You know, very much manual process where you get all these, you have to get into the platform and look at the keywords, the specific, you know, L one, L two, L three keywords, and then, you know, use, okay, now how do we, what type of content we should be creating? So, but what we have now, we are using a lot of, a lot of this and being able to show out a lot more content, um, on, on our website is, um, really [00:31:00] looking bright edge, looking at what the market is, is suggesting the keywords, the insights that you're seeing, their intent topics.

[00:31:08] What are strategies, what is the consumption happening on our website, um, as an example. And then, uh, really using this as a way for them to churn out some content briefings around specific, you know, topics and categories. So that's something that we are, we are using, um, at this time. And then we put it in our workflow, um, from a, you know, content QA standpoint, um, which we are, we are working to say how can we integrate that briefing into our, uh, you know, our, our Microsoft copilot, um, for us to even come up with, uh, an article which can.

[00:31:43] You know, then just be pushed into our CMS. Uh, that's something which is work in work in progress. Um, but that's something which we are, we are using, um, you know, a lot, which is combining what our web data is combining, um, you know, what our, what Bright Edge is looking, seeing from [00:32:00] their research, um, and then using that to recommend content, um, and content briefings from there.

[00:32:06] Um, the other one, which we have, have done and uh, used is, um, six Sense Predictive Model. Um, so we, um, um, implemented, um, six Sense, um, a few years ago. Um, and we really, um, we built this predictive model where, um, we could see. Where accounts are in what buying stage, um, and more importantly, where are the accounts, you know, within our ICP who we were not even aware, you know, this whole thing about the doc funnel, uh, because that's, that was a problem, um, is we were just, you know, you were limited to going after an X number of accounts and the data was suggesting, well, what about these additional accounts?

[00:32:52] Because they're your lookalikes, right? Your I and within your ICP. And then you just push them, um, you know, into, into [00:33:00] if you, I, if you determine that those are the ones, you then just push it into Salesforce, uh, for them to get created. As accounts into, um, you know, in Eloqua, and then you can simultaneously push them into a dis, like an advertising, um, campaign because you have all this, you know, great insights, um, you know, from, from the, from their model.

[00:33:21] Um, so we have, we've been using, um, we use that we have now moved away and we've built up, uh, an internal predictive, uh, engine model, which we are again using the same way, but six sense actually, um, you know, had a, has a very good use case, uh, which we, we implemented and we got one a lot of, um, you know, increase in efficiencies.

[00:33:42] Um, but then, and then also, um, a lot, um, in terms of the opportunities that we were missing out, uh, from an activation standpoint.

[00:33:51] Phil: Very cool. Two, two cool examples there. Um, yeah, I feel like different teams are part of the company's growth flywheel, right? Like this idea of [00:34:00] rapid response. Like responding quickly to customer needs, market needs as they're kinda shifting, uh, it needs to be part of a, a team's operating model. I know ops folks think about that a lot.

[00:34:11] Uh, 


[00:34:11] 5. How to Use Rapid Response Teams in Marketing Ops
---

[00:34:11] Phil: in your voice of customer piece that you wrote, uh, on Forbes, you recommended setting up this like rapid response team to tackle feedback quickly. I really like that idea. Like what does a rapid response process look like on the ground for marketing tech teams, marketing ops teams. Uh, there, there needs to be like this rapid response process across all ops teams in, in an organization, right?

[00:34:35] Like marketing ops, sales ops, customer success ops, rev ops. In that case, uh, it could be as simple as like setting up team channels or inquiries. Like curious about your take there, like walk us through that.

[00:34:46] Aditi: Um, yeah, so we, again, like you said this right start simple. Um, for us it's, it's a teams channel. Where, um, you know, we, and again, it's a, so for us it's, um, our [00:35:00] field marketer, field marketing team, our, you know, digital team, our ISR MDRs, um, field a, they're, um, for, for depending upon the segment, um, they're on one channel.

[00:35:13] Um, and what we use that as a way is to, to really, um, you know, triage, um, when customer inquiries as an example. So you get something on the website. Or, um, there's a webinar that was happening, um, you know, LinkedIn live, and someone messaged, um, you know, I'm looking for x, y, Z information. Uh, I cannot find it here.

[00:35:36] Um, can you, can you share more? So that just, um, you know, went into our, our rapid response or our channel, right? And we like, okay, hey, we have this response, uh, who should be acting on it? Um, and then it got resolved like in, in five minutes. And so here is where the, this, the beauty of this simplification is us waiting for things [00:36:00] to be sent, and then that gets routed and then we are expecting SLAs.

[00:36:04] These rapid response teams, um, can just, you know. Give you those aha moments that those customer delights, because, you know, when we say that we need to, uh, to do real time or near real time, um, you know, activations or, or feedback, this is what we are talking about, right?

[00:36:24] Like the, our, our historical way of thinking is someone submits a form and it gets routed and someone is then, you know, you, you wait for a day and then someone, if someone doesn't respond, you reach out to the ISR that, that should, that should all go away. Um, it needs to be done in a way that the moment, and again, maybe there is steering to it, right?

[00:36:45] Like the, the severity of, of what the question is, or the inquiry is. But then you ensure that you are working on it like a rapid response team. Even if it is as simple as, let me connect you, um, to X, Y, [00:37:00] Z because you know, this is something that we don't know right here is the expert, or, um, someone needs an RFP.

[00:37:07] Actually we got an, we, we even get all these inquiries about, as an example, employer verification. Um, right. And, and so this is something that we have just been able to solve for like in, in, in less than an hour. Um, because it's, it's one channel. It's one place where everyone comes in, um, and you know, we determine what the type of request is and you solve for it.

[00:37:30] And we need that, I think across every. Business function. Um, but then that brings the complexity of, well, how do you then share all this great, you know, information or rapid response, um, that's happening across teams. And again, this is where I feel like, um, AI can be a great way for, um, for, for what this orchestration to work, um, beautifully.

[00:37:55] But for me, like that's a simple use case without any, you know, major [00:38:00] automation, you know, AI use case, uh, of rapid response. Um, it's just every, everything we manage through a team's channel, and it happens beautifully. And there is accountability because these people know that they're responsible, um, for, for X, y, Z or for a specific part of the, of the business.

[00:38:19] So it needs to start simple. Like it'll start simple, but it needs to start.

[00:38:26] Phil: Yeah. You, me, you mentioned the, the cultural piece there and the collaboration piece. Can, 


[00:38:31] 6. Building Customer Obsession Into Marketing Culture
---

[00:38:31] Phil: can you think of like cultural programs that you've implemented to keep teams aligned with, like the reality of customers, like customer problems of the day, things like internal newsletters or just like meetings that you have internally that are outside of like those teams channels or even like KPI incentives that are tied to customer satisfaction.

[00:38:51] I feel like everything being proposed is, you know, something that, like, it starts with like a digital program, customer initiative or new [00:39:00] logo campaign. Like it needs to start with why, like what is the customer insight? Do you agree with that? What are your thoughts there?

[00:39:05] Aditi: Absolutely. And I think that there are different ways, like you said, um, you know, I have in in, and I have been pushing for it as a, as a culture change at least, um, in marketing. Is every, every brief or however, uh, every brief, every proposal that you're bringing in needs to start with, uh, a customer insight.

[00:39:29] Why is this? What, what is the customer kneeling here? Why are you proposing this? What problem for the customer is this going to solve for? I, and I'll tell you Phil, it's difficult. Um, you know, because it's like you're changing the. The DNA of, of, of a, of a company, of, of a team. Um, but these are, and this needs to, you need to think of it as, as tops down, um, is you have to build that, that [00:40:00] discipline, um, you know, um, in how you operate.

[00:40:03] And you do the same walking in every like, and, and letting them know how, how you approach at solving problems. But it needs to, so for us, every, every meeting, every proposal has to start with a why. Like what is, what is a customer inside that is driving this? The other thing which we, which for us has been very effective in our, in our organization is we have this, um, um, standup.

[00:40:33] So for us it's a, we call it the Digital Customer Experience Council. Um, but it's a. Monthly cross-functional meeting that we have, um, you know, which is attended by product, by cx, by marketing, uh, by, sorry, by GTM teams where we share, um, you know, um, what we are working on, but more from a customer standpoint, [00:41:00] right?

[00:41:00] So, well, there is a, a, a, a customer unification program going on in the product team as an example. So that just gives us more information, like am I, like in marketing to really think of, okay, what are they doing? How can we cross pollinate? Are there areas of integration or efficiencies we can bring in?

[00:41:21] Um, you know, we are right now. So that's, that's the type of, um, um, I think, um, way that is helping at least people understand, um, how do you really share these customer themes and this. You know, competitive information that someone else is using for their own, you know, needs. But then how we can incorporate it in our competitive takeout campaign, um, you know, as an example.

[00:41:48] So, so like that's, um, that I think is, is another, um, excellent way, um, in an organization as you, you're building, you know, that, that culture, um, of how, of how you do it. [00:42:00] Um, and then that's the other thing which, um, which we are, we are getting to is, um, that the, every, every meeting, like every strategy deck, everything that we do needs to start with the, the, the slide, like needs to, like slide word dog needs to start with a customer insight.

[00:42:20] Like that's the other thing. It's, again, like I said, takes time, but these are few things and it's, it should be at every level, right? Like it should be even at a CEO. Um, you, you know, at the CEO level is you, you, you need to show, um, that you are breathing, like you live and breathe, um, you know, customer, customer sentiment.

[00:42:42] And that's how I, I think that you, you know, um, these customer obsessed companies get built, this customer obsessed, um, cultures, um, get, get created, um, and just, it's easier said than done. And therefore a lot of companies and [00:43:00] executives say, we are customer obsessed and customer first. You need to really wonder, is that truly, truly the case?

[00:43:07] Phil: Yeah, I'm, 


[00:43:08] 7. Why Voice of Customer Works Differently in B2B and B2C
---

[00:43:08] Phil: I'm curious to ask you about the difference between B2B and B2C. 'cause you've had experience in both B2C, like at Castrol dealing with consumers and dealers, and now you're in B2B at Teradata, more like enterprise side of the world. How does voice of the customer differ between both industries?

[00:43:25] Like are B2B companies doing enough to really listen to customers, or can they learn more from like the scrappy B2C tactics that you've kinda used in the past?

[00:43:36] Aditi: The, the, it's the two. Um, I would say, um, it's, it's, it's, they're different in terms of their maturity, right? Like P two C we talk about is, is often. Anecdotal, uh, messy, but it's fast. Um, and B2B is often formalized. Right. But it's, I I, and it's, it's slow and it's, it's risk. It sometimes feels also [00:44:00] risk averse.

[00:44:00] Um, right. Like, I, I would not now dream of just picking up a phone and calling a customer to say, can I speak with you about, about this? We, we just, we do that for, we did that when we were, we were selling, you know, like Pepsi or we felt when I, when I was selling. Um, engine oil. Um, but I also think it's, I like, I think B2C does a really good job of like gorilla listening ride alongs and store visits and social scraping.

[00:44:30] And B2B is a lot about structured listening, you know, all the customer advisory boards and the win loss and the, you know, Q bs. Um, and then like I, I already, um, I think that there's also that emotional aspect, right, which is very, which is often very visceral and, and reactive. Like, I, I, you know, this, this sucks and like, why, you know, your, your product just sucks and you promised me X, Y, Z and you never gave me that.

[00:44:57] And the B2B emotion is, [00:45:00] you know, often, um, you know, strategic and rash, uh, and rational, you know, but of course very much high stake. So it's the, you know, there are very, there are these key, key differences that I think are, are there in, in both, uh, the models. I think when B2B can learn from B two. C is, um, you know, closing the feedback loop like visibly and, and often, right?

[00:45:26] Because in B2C, when a customer like complains on social, the best brands respond like publicly and update them on the fix, right? That visible builds trust. Um, you know, in B2B I do wonder like feedback probably goes into a black hole unless it's like a top 10. So we that,

[00:45:47] Phil: we'll make sure to put that on the product roadmap and we'll, we will tell our product team about that. And you're like, no, you won't. But thanks for pretending to.

[00:45:54] Aditi: right? Exactly. So I think that that, that, that B2B should be adopting a lot of visible, [00:46:00] like we heard you moments across channel, right? Showing that that feedback from a ticket or a QBR, whatever that was drove, um, you know, real action. And then I think, you know. The other thing which we, which B2B can certainly, um, learn from B2C is simplifying the message.

[00:46:19] Um, even if, you know your product is, is complex, right? Um, if it, so it's like when, when marketing you to mechanics, um, you, you learn if it, if it can't be understood at a gas station or a garage, it would not, it won't be used. Uh, right? So complex doesn't mean to, doesn't have to mean complicated. Um, and we, a lot of times in B2B we often.

[00:46:44] Over contextualize, I dunno if that's how you pronounce it, like value props. Uh, but clarity wins deals. Um, so you, if you have to think of like using VOC to pressure test, um, do customers repeat your value back to you the way you [00:47:00] say it? If not, you know, your messaging needs work. Um, and so that's, that's there.

[00:47:06] Um, B2C I mean, we can go into, and then I already talked to you about like scrappy listening in B2C beats over engineered systems. So B2B needs to do to do that, right? It's not about scale, it's about the proximity, um, um, to the, to the truth. And B2C can learn, you know, how do you really operationalize VOC into strategy and roadmaps because, um, you know, B2B does that really well.

[00:47:32] Um, sometimes to their, to their, to their.

[00:47:35] Phil: they're detriment.

[00:47:36] Yeah. 

[00:47:37] Aditi: To their, to their, uh, detriments. That's what I would probably think of, you know, as takeaways from, from both of the, each of the world.

[00:47:46] Phil: yeah. No, love your thoughts there. Addie uh, conversation is flown by. 


[00:47:49] 8. Why Life Integration Works Better Than Work Life Balance
---

[00:47:49] Phil: I got one last question for you. You're a marketing and a rev ops leader. You're a VP at a big company. Uh, you're also a writer and a well traveled speaker. You're a mom. And, uh, one question we ask everyone on the show is, how do you remain happy and successful in your career, and how do you find balance between all this stuff you're working on while staying happy?

[00:48:10] Aditi: That is a difficult question, Phil, and I probably think a lot, um, about, about that. Um, it's about do you, do you feel happy and energized when you wake up? Um, you know, every, every day. Um, and. And for me, like I use that as my pressure test to, um, you know, assess, um, how what I'm doing is to something which, you know, is making me happy.

[00:48:49] Um, making me, uh, more, uh, mindful of how I, I add value, you know, to my family, uh, [00:49:00] to the company that I work for, to my community, to my friends, um, and to myself. Um, so for me, I think that, um, that mindfulness about these, these multiple spheres of life, um, and how I am I'm doing across this, um, you know, really boils down to.

[00:49:23] When am I excited to do, like, get up every morning and get into the craziness? Um, you know, the, the world, um, that we, we live in, because I don't believe in work life happiness there. I I just think that there needs to be a lot of, um, how do you say, integration of the different aspects of your life. So it's work, life, community, personal, family integration, um, that, uh, you know, you need to take into, into, into account as you are thinking, am I happy?

[00:49:58] Am I [00:50:00] enjoying what I do? Uh, and do I like running after my toddler? Uh, but yeah, that, that's what, that's what I guess makes me happy. Um, or, or I use to determine, uh, yeah, what do I do next?

[00:50:15] Phil: Yeah. I love it. Whether you like chasing your toddler or not, the sad reality is you're, you're gonna have to chase the toddler no matter what.

[00:50:23] Aditi: Yes.

[00:50:24] Phil: Don't put your finger in that. No. Drop that. Don't, don't pick that up.

[00:50:29] Aditi: Yeah, it, it does determine how I react to it.

[00:50:33] Phil: Yeah. Yeah. A hundred percent Addus is super fun. You really appreciate your time. Thank you so much for joining us.

[00:50:38] Aditi: Of course. Thank you so much, Phil. Thank you for having me. I'm looking forward to seeing my avatar.

[00:50:43] Phil: Yeah,