Today on the Demand Gen Pod, Episode 27, The transcript discusses the significance of a Martech stack in marketing, emphasizing efficient tool integration. Ryan details how combining tools can boost efficiency and enhance customer experiences. Consideration of business goals, audience targeting, and marketing objectives is essential for building and optimizing the Martech stack, as well as focusing on automation with Zapier for streamlined tasks.
Efficiency shines through automation examples using Zapier to streamline tasks. Data-driven decision-making, improving customer experience, and evaluating tools based on functionality, scalability, integration capabilities, and cost are also highlighted. Best practices suggest regular process reviews to remove redundancies and the implementation of marketing automation for repetitive tasks.
Integration points in the data flow are crucial for establishing seamless ecosystems across platforms. The discussion ends with an invitation to subscribe to the Demandgen podcast hosted by Ryan.
Summary notes from Episode 27:
Chapter 1: Understanding Martech Stack (00:02 – 01:34) 00:02: Introduction to
Martech stack and its purpose in streamlining marketing processes. 00:33:
Importance of efficiency, data-driven decisions, and enhancing customer
experience through optimized Martech stack. Chapter 2: Building and Optimizing
Martech Stack (01:42 – 04:02) 01:42: Considerations for building and
optimizing Martech stack based on business goals, audience targeting, and
marketing objectives. 02:10: Focus on functionality, scalability, and
integration capabilities when selecting tools. 03:28: Example of optimizing
tools based on business needs and scalability. Chapter 3: Streamlining
Processes for Efficiency (04:17 – 07:58) 04:17: Benefits of streamlining
processes, reducing manual effort, and integrating tools for efficiency.
05:15: Automation example using Zapier to streamline email testing processes.
07:58: Converting efficiency into data-driven decision making and enhancing
customer experience through personalization. Chapter 4: Essential Components
of Martech Stack (10:19 – 11:50) 10:19: Overview of essential components: CRM
system, analytics tools, and automation platforms. 10:46: Criteria for
selecting tools: functionality, scalability, ease of integration, and cost.
11:50: Importance of seamless integration for workflow efficiency and
automation. Chapter 5: Establishing Data Ecosystem and Best Practices (12:45 –
15:04) 12:45: Leveraging tools like Zapier for seamless data ecosystem
integration. 13:49: Importance of clear data pathways, source of truth, and
consistent data structure for cohesive insights. 14:07: Best practices include
regular review, eliminating redundancies, and utilizing marketing automation
for efficiency. Chapter 6: Conclusion and Next Steps (15:04 – 15:18) 15:04:
Summary of key points and best practices for optimizing Martech stack. 15:09:
Invitation to reach out for questions or feedback, concluding the discussion
on Martech stack optimization.
Full Transcript:
00:02
Good morning. Welcome to the demandgen pod. My name is Ryan, and today we are talking about our Martech stack. And specifically we’re going to be talking about building and optimizing it. So this is, I think, actually going to be kind of a quick one today, but let’s get going. So. All right, Martech Stack. Right. What is it? It really simply, it’s just the combination of marketing technology tools to streamline and optimize our marketing processes. And that might mean our marketing automation tool, it might mean Salesforce, it might mean tableau. If you’re doing some sort of bi stuff on your reporting, it could mean Google sheets, it could mean anything that falls under any of those categories. Okay. And the reality is that all of these tools inside of our Martech stack, they ideally work together.
00:58
So if you have data coming into your marketing animation tool, it syncs with Salesforce, or it syncs with whatever CRM tool you’re using, Monday.com or whatever the other various options are. If it is that you have lead forms and they’re Google forms and they’re going into Google sheets, that Google sheets then passes that data to somewhere else. That is the ultimate goal. And the reason this is also important is that it’s pretty straightforward. It enhances our efficiency, enables data driven decisions, and improves the customer experience because is we can make sure that whatever customer data we have going in one area is going in another area as well at the same time, or at least close to it. So what should we consider when we’re building and then also optimizing our martech stacks, we can think about the needs.
01:42
So what are the business goals, what are the audiences that we’re targeting and what are the marketing objectives? So this can also go beyond our CRM tools and also into the actual marketing side of things, paid and email and all of those things as well. So when you’re thinking about what you need, consider your functionality that you’re requiring, consider the scalability of those tools and really importantly, integration capabilities. Right. And also then for the optimization side, we can think about reviewing and updating the tools, making sure that all the tools that we’re using are aligned to business goals. And then also what are the benef, and then also just how they all work together. And so just kind of an example of this, right? So an example of this for us was that were using several different tools actually for the podcast specifically.
02:36
But even with clients, we will use tools. And were using a tool called email on acid to test all of our emails, and we ended up actually switching over to litmus. And the reason that we did that was because the frequency that were using it and the sort of the structure that email on acid, even though it’s great that it uses in terms of getting extra accounts for people, it actually just made more sense, scalability wise, to use litmus. So we ended up having annual subscription to email and acid. And when that ran out, we moved over to Litmus because we realized inside of our text track that we ultimately really needed to think about what happens if we add another team member. What’s the cost there?
03:17
And even though it might only be a few hundred bucks a year, and it’s not necessarily all that expensive to add somebody, it can add up. And so when you’re thinking one at a time, maybe not such a big deal. What happens when it’s two, three, four and you’re talking about thousands and thousands of dollars a year? What does that look like? This can also stream, this can also reach over into things like email marketing tools. When you’re thinking about an email marketing tool, and I think we had an episode on this, too. What happens when you’ve got 500 people in there? What happens when you have ten? Probably not that big of a deal. What happens when you have 10,000 because you’ve grown? What does that look like in terms of cost?
03:56
What does it look like in terms of workflows that you can create? How complex can you make them? Will the tool be able to grow with you the way that you need it to? And we don’t necessarily always know how a tool needs to be able to grow. You know, we certainly don’t a lot of the time, but we can at least guess and make educated decisions. So with the efficiency side of things, you know, we can really streamline those processes. We can reduce manual effort.
04:24
A lot of what nurture labs does, for example, is they really focus on streamlining and reducing manual requirements by integrating tools together, even if they’re not supposed to be integrated or should not be able to be integrated, we try to find routes in order to be able to pass data from one to the other so that they are. And it’s funny because this actually came up just today, actually, were doing testing for client emails, and the client emails were for, in total, there are about 28 emails. And we had actually built a Zapier program for a different client. And the way that it worked was that we had, when a test email got sent, we would send it to a special email address and that email address would then go into Zapier.
05:15
Zapier would pick it up, it would find the view as a webpage link, and then as soon as it found that link, it would grab it, send it over to an API, to a tool to grab the screenshot of that view as a web page link. And then it would take that and then it would put it into a Google sheet. And this is really neat because when were doing this for our other client, it was like almost 100 emails that were trying to do. And that’s just so cumbersome to do manually. So we realized that it would make sense to spend several hours to build a process that would allow us to automate this. And the big reason for that is because the alternative is what happened to me today. We didn’t have this set up.
05:52
And instead what had to happen was that I got a test email from the team. That test email goes into my inbox, right? And then I open that test email and I see the subject line, and then I’m looking at all the various subject lines again. I think it’s like 28 emails. So you’ve got 28 subject lines to look at to figure out which email this actually is. Just in case I didn’t get sent an order or delivered an order. And then once you have that, you go and you find the view as a webpage link.
06:15
You open it, you copy it, you put that into Google sheets next to the correct email name, and then you kind of set up Google sheets so that we have, like the email name, the subject line, the view as a webpage link, and then, you know, round one QA notes, round two QA notes, etcetera. And this all comes into play because at the end of the day, this has taken me so long, and I really wish, even though it’s really simple and there’s nothing all that complicated about it just takes a long time to get an email, look at it, recognize that email not only for a couple of things, right?
06:52
So not only is that email the correct subject line or has the, you know, the correct content or whatever, but also just getting into the right spot to even be able to start making those decisions. And then on top of that, the program would then be able to identify if a new test comes in with that same subject line to create a new column for it. And all of that is done automatically. And so what you’re able to do is actually do the entire test send in bulk, and then it just populates into a spreadsheet and then everybody can just go look at it in real time and it is so helpful.
07:24
So this actually kind of kicked me today because we didn’t do this for this program and I kind of wish that we had because in hindsight I spent probably 2 hours this morning not just having to do all the links, but you know, maybe 20 minutes setting up all the links and then you know, maybe half an hour going through all the data and the content and then sending them back to the developers to have them fixed and then do it all over again. Right. So that’s been a lot of my morning today and that actually gets really frustrated by the end of it. So, really thinking about efficiency, can make a substantial difference. You can also then convert some of that into data driven decision making by looking at the data on in real time, which is very helpful.
08:07
And then, you know, like I mentioned, enhancing your customer experience because you can use that personalization engagement. And while that’s not really explicitly related to my anecdote, you can certainly see how getting form data to the right places, whether it be to sales or marketing or triggering emails based on all of those things, can be really helpful in real time or near real time, or based on the time that something is submitted or an action happens. So you can go through identifying some of the tools that you could leverage by looking at an assessment of different marketing tools, aligning those to your objectives. You can think about not only who you actually market to and then what they might benefit from, but also the budget and then the desired outcomes.
08:56
And then you can sort of start by just saying like, what’s a pain in the ass for me today, right? What’s difficult? So here’s how you start. What is causing a lot of taking a lot of time, what takes time, and if we understand what takes time, we can then think, how could I make that better? Right? So just in my tra, in my testing example for QA, I already knew that the system worked, I just didn’t set it up. But I remember when were planning on doing the testing for those 100 emails, I thought, gosh, this is going to suck. I really don’t want to have to go through this for every single round.
09:30
I think we did three or four rounds, that’s 400 emails that’s getting looked at and that is actually getting looked at by, I think, a team of about seven. So we’ve got seven people relying on data to be exactly where it’s supposed to be. And that’s a lot of work to do manually. So if we can automate any of that, then that really helps. But even if you were looking over into your to your marketing automation tools or your CRM tools, what is a pain right now? Is it tracking leads? Is it knowing where they came from? Is it being able to tie leads to revenue, or tie, I guess, contacts or opportunities to revenue? Is it trying to understand why people were closed, lost? Is it anything along those lines?
10:11
And there might be tools that can help you to identify some of that reporting and take some of that pain away effectively. So what are some essential components of a Martech stack? So I think we kind of covered them, but there are some new ones as well. Your CRM system customer relationship management. Pretty straightforward. We need one for effective communication, analytics tools for tracking and measuring marketing performance, and then any automation platforms that you can streamline repetitive tasks for increasing efficiency, which is, you know, Zapier is what we really use to do that. So to help you choose the right ones criteria, let’s think about functionality, scalability, ease of integration and cost. Okay, functionality, scalability, ease of integration and cost. For evaluation, you can leverage trial periods or user feedback, compatibility testing.
11:06
I actually found, honestly, for me, it just depends on how you actually search for things. But for me, I use Reddit a lot to identify really solid feedback on different tools, products, et cetera. Reddit Reddit can be quite a path down, quite a weird, quite a way down the wrong path if you’re not careful with it. But usually taking an approach of searching for something in Google and then putting Reddit at the end of it actually gives me some really good feedback on various things, including Martech stack tools. After evaluation the integration, scalability, make sure that they can integrate with each other. This was something that I took into consideration when were developing the podcast because I wanted to make sure that our workflow was seamless.
11:50
And our workflow is so good on this podcast that I have everything set up where by the time I finish this episode and it saves as a file, I drag it into a folder and everything gets created for me. The blog post, the automation for social stuff, the transcript gets created from the video automatically. It takes the video and converts it into an mp3 to be used on Spotify. All of that stuff is actually automated. And the reason why I’m able to automate it, I do it with the help of Zapier, which is really fantastic.
12:26
But the reason why I’m able to automate all of that is because I chose tools intentionally that worked, not necessarily together, but at least with Zapier, because it’s very difficult sometimes to find tools, especially across different multiple platforms and things that can really work together or purposes, I guess I should say not necessarily platforms that work together. And so Zapier really lets you leverage them interesting ways, and that’s what we do with the podcast. What about integrating all of those to create a nice seamless data ecosystem? So the data flow should really be based on you working to establish clear data pathways and integration points. At what point do you need data to flow? From a to b? From a to c? From a to d? From d to b, right? You get the idea.
13:16
What points do the data have to go that way? And then the other thing I think is really important is always having sort of a source of truth for something really relevant for CRM data. When you have that understanding, you can structure the data and implement it in a way that is consistent across all of your tools. And that sort of facilitates this cohesive insight, allows you to get better targeting, better personalized experiences when all those tools are working together kind of seamlessly. A couple of best practices as we wrap up here, regularly review and update your processes. Eliminate redundancies. If you realize that you’re paying for two tools that do kind of the same thing, is there a way that you can merge that data together to be able to not have to pay for two tools?
14:07
And then inside of your automation, implement marketing automation for repetitive tasks, you can use your marketing automation tools. You can use them to manipulate and clean data. An email program, think of wait seven days and then send an email. Wait another seven days if they didn’t open it, resend it, things like that. Things like that. You don’t have to send emails in that you can just put people in them and then manipulate the data as required through various filters that meet certain criteria or meeting criteria at a certain time. You can use your marketing automation tools to automate data process cleanup, and that’s really powerful. And at the end of the day, all of that allows you to reduce those manual efforts, streamline your workflows to save time and resources, and all of that fun stuff.
14:57
We’re basically at the end here, but I’d really appreciate it if you took the time to subscribe as that is right in front of my face. And we will see you next time on the Demandgen podcast. My name is Ryan. You can reach out to us at hello@demandgenpod.com if you have any questions, or you can type the questions right into Spotify. There’s a little box there to ask a question. It comes right to us. I’m really happy to answer. Thank you very much and have a great day.