[Music] [JJ Raymond] Welcome to our session today. I really appreciate y'all making the time to come out and hear us speak. I'm JJ Raymond, and I lead our Marketing Data, Technology and Innovation team here at Nasdaq. I spent the last 17 years in tactical and strategic roles related to different sales and marketing technology systems. I ended up at Nasdaq actually by way of acquisition, after spending eight years as a VP of Operations at eVestment, where I was leading the team that ran, kind of, the internal operation systems related to marketing, sales, service, finance. And most recently, I've been at Nasdaq leading the group responsible for marketing automation, marketing operations, reporting, business intelligence, as well as customer data.

And with me here is Sasha Andrianova, and she's a Data-Driven Digital Marketer turned Marketing Systems Strategist. For the last four years, she supported Nasdaq in driving our digital maturity through SEM, ABM, sales enablement, multi-channel orchestration, and technology implementations. She's had both administrative and user experience with our best tech stack and she served on our CDP team directly, helping roll out the platform and expanding data interconnectivity at Nasdaq.

I want to talk quickly about what we do at Nasdaq. Almost all of you probably know the Nasdaq name, and you probably think, stocks.

But that's only a fraction of what we do. The software that powers our stock exchange is also powering about 130 out of the 170 other global stock exchanges.

We also compete with one other organization in the US that I won't name.

For companies going public, and over the last 5 years, we've won 74% of those new listings. So about three out of every four private companies these days are going public with Nasdaq, something we're very proud of. We're also tightly integrated with the banks across the US. And they use our AI-powered anti-financial crime software to automatically identify fraud in accounts around the world, prevent those transactions from ever happening in the first place. We also have a really good story on the website about how we helped end a human trafficking ring.

So now that I've talked about the state of data, both in the world at large, as well as in our world at Nasdaq.

These are some of the challenges that Nasdaq has experienced firsthand in the last few years that are probably being felt by most global marketing teams right now. The volume of customer data is expanding exponentially due to the proliferation of digital channels. This growth includes not just traditional structured data, like CRM data, but also unstructured data from social media, IoT devices, web content, not to mention all of the content being generated from AI and machine learning.

This variety and volume of data make it increasingly challenged to manage and analyze it efficiently. As the sources and the types of data multiply integrating this data into a single cohesive unified view becomes very complex. Organizations often struggle with siloed data residing in disparate systems and databases. I know we certainly did. Effective data integration is critical for comprehensive analytics, insights, and it necessitates the need for advanced solutions and strategies for seamless data flow across all of those platforms. And but the introduction of stringent data protection regulations like GDPR in Europe, CCPA in California is a heightened focus now on the privacy and security of customer data that we didn't see a few years ago. Companies must navigate these regulations carefully to ensure compliance while still leveraging that dataset for automation, reporting and insights, to ensure that the business can function normally and optimally. Here's a quick stat to, kind of, bring it home on privacy, but for especially severe violations of GDPR, the fines can be 20 million euros or up to 4% of your previous year's total global revenue. So the fines can be massive for non-compliance. There's over 25 different technologies contributing thousands of data points related to our prospects, our users, and our clients. Our marketers are constantly asking us for access to all of them in order to target their marketing campaigns better and understand specific user behavior. Marketo and Adobe CDP are at the core of all of these systems, as they allow us to really build this massive, unified database and execute campaigns with highly targeted audience segments.

Now that we've established that data is becoming more complex every day, I want to talk about how our business is changing every day and how we can manage that change and try to stay one step ahead.

As Nasdaq's grown over the years, we've been regularly confronted with new business needs and requirements that the current tech stack can't handle. First challenge we face is the growth in the number and size of all of these internal systems. It seems the new product is launched every day, and the salespeople have always promised that it's going to fix everything in your org. And so we buy it, and we plug it into the web.

Don't get me wrong. Growth is a positive, and it's necessary for every single business.

But it requires that we match the right tools with the pace of that growth to ensure that the organization can continue to grow and scale rapidly. This growth in internal systems means that the data records are scattered all across different platforms, tools, databases, none of which communicate with each other.

When I joined Nasdaq, we had upwards of 15 different connections just in Marketo alone.

Some of those were custom built connections. Some of them were in the connector library.

This led to a lot of complex and error-prone manual efforts to compile and rationalize list outside of those connections. And all of that effort was required just to send a campaign and maybe understand the recipient's basic interactions. Tracking activity across other channels was an even more daunting task that many didn't tackle.

And lastly, we were also dealing with, a decentralized tech stack due to our divisions being more of a federated setup under a single brand. So each division or business unit, they have different platforms that they employ across their marketing and sales teams. Often, there were different instances of the exact same platform, sometimes even multiple instances of the same platform within a single division.

So we've always been challenged with the large web of systems and data silos. However, one of the situations that may be less common for everyone here, and is exponentially more challenging for us, is incorporating growth from acquisitions rather than organic growth. Nasdaq's made over 20 acquisitions in the last 10 years, and the 2 largest at $2 billion and $10 billion were in the last 3 years. So when these acquired companies are folded into the Nasdaq brand, oftentimes, their operational systems are left siloed for some period of time after the brands are merged, and this creates difficulties, such as overlapping audiences, receiving conflicted or off-brand, messaging, or even excessive communications. So ensuring that the activities and the data fields particularly privacy and consent fields from each tech stack are united and usable across the organization can be a huge challenge, particularly when you're mapping custom objects that don't always match to the objects in your core system.

Another challenge we had is satisfying the sales team's hunger for cross-sell information immediately after the acquisition is finalized. The day it's over, they come and they say, where's the list? This is often a significant benefit in the overall synergy calculation that was done for the deal. And so finding ways to quickly unite the customer information between these platforms for analysis and outreach can quickly become kind of an all consuming fire drill for every group, filled with complex, sometimes conflicting datasets, non-standard integration points. It really just becomes a challenge. So finally, tracking the user activity across these platforms, websites, apps can become a really insurmountable challenge for some small teams. This directly translates to a loss of visibility into the full funnel, as data is really lost when users transition, say, from that Nasdaq website to an acquired company's website and back again. And this fractured view of client activity can quickly cause executives and users to question the validity of the data as they see many data holes appearing in journey.

There are seemingly endless list of challenges we face, as the company grows and the world grows, but one of those major considerations is managing data privacy, like, I talked about earlier. For example, when a person makes a request to exercise their right to erasure or the right to be forgotten, it's the obligation of that company to locate every single instance of that person's personal data and remove it from their databases, their lists, their systems. This can become an unbelievably and nearly impossible task with so many disparate systems and data sources if they're not connected.

The final technical challenge... Oh, sorry. Another difficulty that grows as time passes is all of these legacy static lists that are all over the place.

Many of them are living in programs like Excel, or Microsoft Access, or uploaded on an internal site.

But the data sources don't get updated with the latest and greatest information, so teams are operating on stale or even completely incorrect information. And the final technical challenge we'll talk about is the pace of new data field creation. Our organization, just like many of yours is growing and expanding every day. And this necessitates the need for new fields, new data values, new objects to meet the needs of the company. This explosion of fields, though, is occurring across many apps and ensuring that all of these fields are not only mapped together but rationalized into a single usable profile can be highly complex and time consuming. So I'll leave you with a few shocking numbers to reflect on. Back in 2016, the Harvard Business Review calculated that bad data cost the US economy $3 trillion in a single year, and that trend continues today. And in 2022, Gartner estimated or they talked about the 1-10-100 Rule. And so when you're bringing a record in, it costs $1 to verify and correct it at the point of entry.

If you wait and correct it later, it costs $10. And if you don't correct it, it'll cost $100 because of all of the cascading implications across different groups.

So at this point, you're probably thinking, "Wow, JJ, this sucks. This is totally depressing. These challenges seem absolutely insurmountable. I only have a tiny team." Yeah, this sucks. I get it. But I want to tell you there is hope. So I'll talk briefly about our vision for the future at Nasdaq, but it likely matches closely to the future that many of you might be envisioning for your own organization.

So for years, we've all been adapting Marketo and pulling it in different directions, making it serve many different roles, including being our master database. But with the continual advancement of both the tools around us and the demands of our users, we need to move beyond just adapting those tools and forcing them to do things that are non-native and start evolving those systems to meet the challenges of today, as well as tomorrow.

Some of you are still hearing all of this and thinking to yourselves, I don't understand why I need another system to manage my data. Marketo is doing a fine job. And maybe it is for some of you today.

It won't in the future.

Marketo is a great tool to start your journey with, but as you scale your marketing efforts rapidly, globally, you start to struggle to do so with just a marketing automation platform.

Here's some of the specific ways we struggled when we had Marketo alone. So Marketo... I'm sorry, marketing automation platforms, in general, are specifically designed to streamline, automate marketing tasks, such as email campaigns, social media posting, lead generation efforts. But leveraging them beyond that core competency, like, attempting to manage complex customer data profiles, can really lead to a lot of inefficiencies. This misalignment often results in operational bottlenecks as the marketing automation platform may not handle those complex data integrations or real-time data processing that users are demanding, ultimately leading to errors and delays.

Marketing automation platforms also excel in managing marketing specific data, but they might lack the sophisticated data management capabilities of something like a CDP.

Forcing those marketing automation platforms to handle extensive customer data can lead to inconsistencies, data quality issues, and it can degrade the data's reliability for personalized marketing efforts, ultimately impacting your campaign effectiveness and your customer insights. Example is this that we found was when we tried to utilize our website activity data in combination with the demographic. Very basic ask. So something like, I want to target CEOs and financial industry who have visited our main product page. It was nearly impossible for Marketo to do that alone.

As the businesses grow, their data and automation needs become more complex. And marketing automation platforms have limited capabilities to scale up and manage the vast amounts of customer data or adapt to new data sources.

I want to talk about Marketo's evolving role in our business's toolkit. So over the last 10 years, Marketo has served as, kind of, an all-in-one tool for launching, managing, tracking, and reporting on our marketing campaigns. But the complexity that's been introduced into the market over the last few years in the form of additional tools, regulations, new data sources has really stretched that marketing automation platform to the limit. All of this change has created the necessity for you to, kind of, redefine what Marketo's role is in your business and what are its core competencies.

Today, your organization should have a corporate wide data strategy to account for all of these changes in order to better serve your stakeholders and your customers. One of the things that we continually tell our users and stakeholders is that our data is a shared resource across the entire company, and the data is a massive asset to every company. So not having a coherent strategy for how you're going to manage it will just result in dirty, duplicative, unmanaged data that's going to directly impact campaign performance, as well as company performance. By separating data from the core campaign automation functionality, it ensures that each one can be independently evaluated and improved.

Always remember, Marketo was created to be a marketing automation tool, not a data management tool. So I want to pass it over to Sasha and just going to dive deeper into how Nasdaq has partnered with Adobe to meet the needs of our stakeholders and really drive scalable growth for the organization.

[Sasha Andrianova] Thanks, JJ. So luckily, solutions are evolving to meet the rising needs of marketers and the consumers they're speaking to today. So let's talk about how Nasdaq has harmonized Adobe CDP and Marketo Engage to improve both execution and audiences across the organization.

When we think about creating and executing a campaign, an audience strategy is the driver of your operations. Buyers expect a brand to know them without knowing too much or revealing that it does. And to speak to buyers meaningfully, you need to know your audience, how well they know you, and where they're likely to find you. These elements inform your audience creation strategy. And while yes, you can continue building your audiences in Marketo, there's a better way. When we think of how we want to start building an audience in Marketo, we think of the Smart List. The Smart List is composed of different filters that combine static lists, custom attributes, and different activities a person has taken which are recorded in your marketing automation platform. All of these things take time to compile within this Smart List. A user needs to stack those filters on top of one another, check that they're all working the right way. And the first thing you're doing marrying the CDP with Marketo Engage is that you're actually saving time in building this list. At Nasdaq, we've been able to simplify our Marketo Engage users' work streams and reduce the hours spent creating large custom audiences by moving our audience building process out of Marketo Engage and into the CDP. Most evidently, this shortens the amount of time it actually takes to build the lists. If you're creating an audience in CDP and sending it into Marketo, you could just use Member of List filter. One and done. Less evidently, this actually also saves processing time. So on the back end, when you build a Smart List and you're stacking all of those filters, Marketo queries every single filter and every single field in that list against every single record in its database to then create a list of users that match every single record or every single filter that you've compiled. This takes a ton of processing time on the Marketo side. And it's also the back end of priority in terms of everything else that Marketo is doing. It's adding fields to Salesforce or adding leads to Salesforce. Excuse me. It's normalizing programs. It's recording interesting moments. There's so many other things that are going on. And so while your Smart List is processing, there might even be potential room for error there. And also, you are just overloading Marketo and what it's supposed to do. You're inadvertently using it as a database rather than an automation platform and taking away from its core capabilities.

By harmonizing these solutions, you also mitigate the potential for human error in creating those Smart Lists, right? I already spoke to all of those different filters that can come together in creating a list. And complex Smart Lists combine custom fields, static lists, and an increasing number of data points to meet the rising complexity and availability of data, as JJ spoke to. A lot of technical configuration is starting to be needed to build these audiences. And at Nasdaq, not all of our Marketo users have technical backgrounds. And so while our users have learned and adapted to this model, this added complexity really widens the room for potential error in each campaign we run. Beyond initial Smart List setup, Nasdaq has also seen manual review of Excel files, last minute refreshes of static lists, and one-off filters for templates and custom campaigns, which also further widens this potential room for error. Let's look at what this looks like in practice. So if you look at the example here, we see nine filters coming together to check job role, web page visited, form submitted, opt-in preferences, and whether they're in a static list of past attendees. All of these filters need to be manually configured by the Marketo users, then queried against each record in Marketo to create an audience of everyone that matches these criteria. Human time, technical time. So now consider a list informed by the CDP. We have nine filters condensed into two. The person is opted in and they're a member of our CDP list. Instead of building our filtering logic in Marketo, we're migrating to building audiences in the CDP and focusing on one filter here. This creates ease of use and enables marketers to focus on audience activation over technical configuration. At Nasdaq, we've seen a reduction in the human error and increased ease of use across a variety of different skill sets within our marketing automation platform when migrating our audience strategy to be built in the CDP.

By marrying the two solutions, Nasdaq has also freed up Marketo administrator time. So CDP helps bridge that gap of knowledge between less technical users to execute in Marketo. And users can stop building audiences and instead focus on activating them. When Marketo administrators no longer need to focus on reviewing and checking every single campaign that's going to market, they can then actually focus on platform strategy, feature enhancements, bug requests, thinking about how the platform fits into the overall campaign workflow, the end-to-end life cycle of a lead's journey with your company, not just the activation through email. So they have more brain space to look at the bigger picture and also maintaining up to date user lists, training users, increasing feature utilization, and expanding integrations and data connectivity across-systems. So harmonizing these two solutions really creates more space for your administrators to do what they do best.

All of the reasons I've listed already lend themselves to faster execution. We've been able to take our campaigns to market at the same rate or faster at Nasdaq. But not only that, we've actually been able to focus on more meaningful content. Again, as opposed to technical configuration, instead of asking the question, are we speaking to the right people? We're asking the question of how are we speaking to these people? What are we saying? What content and journeys are we delivering? And so we've used that additional time to focus on perfecting persona-based messaging and building compelling content libraries of white papers, fact sheets, and display advertisements that actually speak to where our audience is in their customer journey. By forgoing technical configuration within Marketo, worry more about how you speak to people than whether you're speaking to the right people.

The best part of my opinion is improving targeting, combining data across-systems and datasets to bring in more robust first-party audiences to fruition. When you come back to an audience strategy being the driver of your operations, your technology should enable you to create better audiences and faster. By marrying the two solutions, and with the CDP in particular, you can improve your targeting by bringing together first and second-party data points from your organization's databases and a user's cross-channel engagement without the added complexity and without the added processing time. Further, you can track your customers' behavior through your marketing automation campaigns and log it all within the unified customer profile for better targeting both today and tomorrow based on the actions that they've taken.

So we've seen how harmonizing Adobe CDP and Marketo Engage improves technical execution in Marketo. Now we'll cover how we improved audiences across our organization. As we know, audience strategy is the core to marketing and sales success. So let's take a look. What use cases has Nasdaq unlocked through a company wide data strategy? At Nasdaq, one of the first use cases we tackled is client data management. So yes, our client data does live in CRMs, but it also lives in unique siloed product databases that exist across the organization. We have a number of different products, different solutions, which are all managed by different decentralized teams. And so when a marketer would like to pull an admin or user list, they need to figure out where this is, in which platform or database, identify a product administrator, get that list pulled by the product administrator, connect with a marketing operations team member to then upload this list to Marketo. The marketing operations team member will run a flow to assign a client custom attribute to every person record to indicate that this person is a client. And then the marketer can actually go and filter or exclude based on this list. Now let's remember this was a static list that was pulled. So pull it one day, get a client the next, and our data is already out of date. This really isn't scalable. As we consider the amount of new users, clients that we're getting, the amount of companies that Nasdaq is working with, as well as the growth of our organization, I'm sure the growth of yours, it starts to get impossible to manage pulling these lists on a monthly, quarterly basis and knowing that you're actually speaking to your clients in a meaningful way. So what CDP helps us do is we've connected our product databases to the CDP. And instead of the recurring export of a static list and imported that list into Marketo, we've connected the CDP to our client database through a one-time connector implementation. After establishing the connection, we've built product-specific client audiences within the CDP. And these audiences are dynamic. They update daily, sending in new people and removing others as our client list grows and changes, ensuring more real-time capture of the actual people that are within our client base. What this means is we now have auto-refreshing specific and very actionable lists of clients, which can be used not only in Marketo, but across other channels. Marketers can either target or exclude these lists and audiences through a simpler filtering process within Marketo. And platform administrators have the added benefit of lessening dependencies on custom attributes and reducing fields on the person record.

Moving forward, an additional use case that CDP has enabled for Nasdaq is easing overlapping data headaches. As JJ mentioned, Nasdaq has acquired 6 companies in the last 2 years, 20 companies in the last 10, and we have 4 Salesforce instances alone, multiple marketing automation platforms as well. This has created a lot of potential for overlap across-systems, challenging our ability to see what unique set of products each client has, as well as their consent and preference across all of those systems. So we are challenged in our way to see how does Nasdaq actually interact with every single person. Do they exist in multiple CRMs? How do we overcome that data headache to understand the customer profile through platforms that don't natively speak to each other? Well, we place CDP as that central conduit. CDP helps bring together multiple instances of your marketing automation platforms, CRMs, and as we mentioned before, siloed databases into that single marketing accessible data hub. With CDP acting as that centralized data hub, not only is data across our CRMs and marketing automations platforms aggregated, but data for each user is consolidated into a single profile. Marketers can then segment and slice and dice this aggregated data to meet their campaign needs. And they're better enabled to create unique and accurate audiences which reflect each person's true interaction with our brand across entities. We've been able to grow our confidence in our client lists and cater campaign messages to each particular client's product needs and sets.

The impact that this has is improving audiences across our organization no matter the use case. Upsell, cross-sell, retention, net new truly the possibilities are endless.

And so what do you do once you've improved audiences across the organization, the way that they're built? Well, you're able to expand how you segment them for more effective personalization. Less time worrying about how you're creating your audience lists means that we can utilize Marketo's native features to a more expanded capability, or more efficiently, rather. So we started segmenting our target audiences by persona decision makers, champions, and influencers in the buying process for each product. And once we generated these persona based audiences within the CDP, what we did was we leveraged dynamic content emails within Marketo to target each person with more specific content catered to their role in that buying decision. We've also worked on perfecting multi-email nurture streams. So prospects start in a net new nurture. But once they convert in a particular product set or solution with Nasdaq, they're unsegmented from that nurture and added to a different one that speaks to the product they purchased. They're kept in the net new nurture for other products in that suite. But the client nurtures will speak more to retention, or sending them tips and tricks for the product that they purchased or an upsell nurture that positions products and solutions complementary to the suite that that person converted on. So again, this person is getting a much more personalized journey rather than generalized content of thank you for being a client, or that you're a prospect and we're trying to speak to you. So we're speaking to users as they touch Nasdaq, rather than resorting to generalized communications.

So the CDP backs our improved audiences and marketing automation workflows. And it's particularly powerful because it is purpose-built to connect data silos across your organization. Imagine a world where all your databases, cross-business, cross-function, cross-enterprise, are all accessible from within one system. And you can view a customer's information every touchpoint from across the firm from one unified profile. You're essentially empowered with a bird's-eye view of your customer's journey with your company and how they interact with you.

So at Nasdaq, what we faced was disjointed lists and databases throughout our enterprise. And what we've been able to do with the CDP is synchronize this data by aggregating it into the single unified customer profile. What this has done is it's allowed us to increase our total addressable market. We have increased our total addressable market by 64% over 12 months with the CDP. This is millions more users, known or unknown, that we can speak to advance their journey with our organization.

Additionally, what Nasdaq faced was Marketo started to serve as an asynchronous source of data across-systems. It started operating as that database. But now with the addition of a CDP to our tech stack, we've been able to have CDP as a real-time synchronous data hub. It's always updating as dynamically as our organization does, rather than combining and compiling static lists.

And the last thing that we faced was exported lists were often combined manually and manipulated within Excel.

You might be doing this. We definitely were. We had VLOOKUPs going on. We had a little, like, triangulation of data. It was crazy. And what we've really come into with the CDP is more automated processing, which have enabled our profiles and our lists to stay better up to date, improving data quality, which is the most important thing for an organization in managing all of the dataset that you have. And so what's the point of connecting all of these datasets? Well, it's to harness the power of your dataset. I heard yesterday in a session that 80% of the data was created in the last 2 years. We're swimming in data, and you need to know how to use it well in order to not get lost in it. Using it well, data increases the efficacy of your marketing. Rather than shot in the dark advertisements, emails, and client communications, you can harness the power of your new dataset to ensure a better return on your time, resource, and dollar investment. And once you connect data silos across the organization, you can truly create value out of the data that you have.

So how are you creating value out of this disjointed data? You can unify cross-system preferences into a single profile to ensure privacy and preference compliance when you're speaking to buyers and users that your organization interacts with. Also, bringing all of your customer profiles into one place increases your total addressable market. And once you've brought everybody to one place, you can expand on each individual profile by bringing in new data points that come in and stacking and building up on the customer profile and the information that you have on each person. So when a marketer requests something such as, I want to target everyone who's engaged with my email campaign. And I want them to have a specific title, but ensure that they visited my landing page, and yet they haven't submitted a demo request already, and they're not a product admin of. Instead of looking at this daunting list of fields and data points coming together, you know that you can do it. This is five data points coming in from five unique systems. And it might seem daunting at first. But instead of going, "Well, how am I ever going to pull this list, you know you can triangulate this data within the CDP because it connects to each of those destinations that your organization has." You're creating value out of each individual data point by pulling it together and creating an audience segment that is highly targeted and actionable.

Next step in creating value out of this data is actioning it through expanded campaign opportunities. All of those filters we ran through are business units criteria for a perfect person. And we can layer in demographic and activity data to create audiences of people who all fit this criteria, without the added processing time of doing so in a Smart List, you can build this perfect person in the CDP, build an audience of those perfect people, and then mirror and expand your total addressable market by creating lookalike audiences. So mirror this ideal perfect person set for each business or the existing clients for each business. So then they have entire new audience lists of people that might be best fit to then convert and create business opportunity for their business. Finally, you have all of these different audiences that are best fit for your particular product set or suite of solutions. And you can activate it across channels by connecting destinations to the CDP, and then launching personalized campaigns at scale.

And so if a marketer asks you to launch Google Display campaigns and, as well as paid social, and then segment them into a particular email campaign based on their industry, or then drive them to a personalized web page based on sales content, you're able to do this. Because you can harness the power of your dataset to know what comes next. You're able to meaningfully create a journey that your users will go on. And recognize that activating your audiences is no longer a set it and forget it strategy. You can map out the user journey and lead them down the funnel, not only knowing what target buyers are taking, what actions target buyers are taking, but being able to segment and filter based on these actions enables you to expand campaign opportunities across that user journey.

Adding a CDP to our tech stack has enabled us to maximize the investment and the utilization of all of the tools in this tech stack. Technology is meant to empower your workflows. It supports simplifying your operations and frontline marketing, sales, customer success functions. It helps you execute faster and at scale with less errors.

And so when powered by CDP, Nasdaq has been able to streamline our operations in our marketing automation platform. We've been able to create dynamic audiences in the CDP and send them to Marketo. We've been able to automate these workflows and better leverage Marketo's native capabilities. And we've been able to scale omnichannel execution to meet audiences in the right place, at the right time, with the right message. Ultimately, we're maximizing all of the tools at our disposal, and being able to better communicate with audiences across all of our channels. But without a CDP, you may get stuck in the streamline phase of this journey, as we did as well. As we have many orgs have built complex processes and programs to meet the rising challenges of data, and they're used to operating off them. You know how to build these complex Smart Lists. You know where to get your static lists and at what cadence you need to update them to keep them mostly up to date. However, managing complexities is just an illusion of being efficient. Instead, it's time to make a change to your mindset and operations by going back and finding ways to streamline the work that's already been done. And even though this work gets done, does it need to be as complex as it is, is a great question to ask yourself, or do you have an opportunity to go back and streamline to really maximize how you use your technology stack? Even with a CDP, if you have one today, are you going back and looking at the inefficiencies within your existing processes? How many of your marketers are still using really complex Smart Lists? Can you go back? Can you help them identify those inefficiencies to then further evangelize the CDP at your organization and help embed it into the workflows that exist today? All of this is a critical second glance at how things are working. And now that you know all of the things that can happen when you harmonize these two solutions, before all of this, you need to know how to sell the vision. And for this, I'll pass it back off to JJ.

Thanks, Sasha.

Okay, so we've taken you through how to realize value from bringing the systems and the data together, but I want to walk you through what might be not the hardest part.

Selling this value to your leadership team and making the ask for the system and the resources.

So quantifying the ROI is one of the most challenging parts of getting a product like CDP added to your toolkit.

However, for your executives, ROI might be the only part that many of them care about.

We've laid out four areas where we've seen quantifiable returns and some suggestions on how to measure those. First, being able to target new audiences that were historically difficult to target, as well as communicating with audiences in a more personalized way using data points that were previously inaccessible. And to quantify this, you can measure uplifts in campaign performance, including clicks, conversions, as well as measuring audience sizes that are sure to result from bringing in a CDP. Second, you'll see a return by reducing time spent on manual and batch tasks related to data transfer manipulation due to having the data located in so many different systems and silos. Measuring the ROI here was done by monitoring the time that specific tasks, such as pulling lists, merging data, manipulating, and deduplicating data, took prior to the implementation of CDP, and then comparing that to the time spent once the CDP is activated and extrapolating that out across the full user base. You can also see the growth in your overall data base size due to the inclusion of records that previously were not included in the audience pull it all.

We achieve significant synergies by aggregating data across CRMs, marketing automation platforms, as well as other systems to identify and unlock sales expansion opportunities such as upsells, cross-sells, renewal prioritization. This may be one of the most important metrics that you can quantify. The increase in pipeline and revenue due to the identification of these new opportunities based on the previously inaccessible data is a key point for many executives. Our final area of return was that we saw a faster time to market with our marketing automation campaigns. And you can measure this by measuring the uplift that you get in operational efficiency. So we really measured the amount of time that it took to generate the campaigns and then measured it after we had the CDP to see the reduction in time.

There's many challenges you'll face when you're trying to win over your executives, but all of those challenges are surmountable. If you take a thoughtful approach and ensure that your executives have an easy decision to make, whether it be concerns about implementation time, system and resource costs, or the magnitude of the change management process for introducing a new system to potentially change resistant team. There's ways to address all of those.

Here's the approach I'd recommend for getting your leadership team excited. First, you really need to build consensus around the opportunity at hand and the potential short and long-term rewards. So emphasizing how a CDP can combine data from nearly all of your internal data sources into individual unified records for every known and unknown person.

And this will enable deeper insights into customer behavior, preferences, trends. This comprehensive understanding also allows for more informed strategic decision-making and personalized customer experiences. Designing a data-driven culture at your organization will provide opportunities for years or decades to come. Second, I'd stress the organization wide impact. Today, the majority of the sales opportunities are influenced by marketing in one way or another. So these improvements at the top of the funnel cascade down through the funnel, ultimately resulting in additional revenue. Better data will also improve your customer experiences across nearly every functional group.

I'd also encourage you to sell the vision, not just the software. CDP should be viewed as a strategic enabler at your organization with benefits across the company. The ROI, at times, might be harder to quantify depending on your organization, so sell the vision of how it can transform your business rather than selling the technical benefits of a tool. And lastly, I'd focus on the quick wins and the specific impacts across multiple departments and functional areas. Whether it be your marketing team, your sales team, customer service, finance, there are many recipients of the benefits of having a unified dataset.

Ideally, organizations that employ a company wide data strategy like this will see tremendous long-term results, including creating a clear vision and a plan for growth, as well as access to an unrivaled database of your prospect and customer data. And it'll really power your marketing efforts for many years to come.

Hopefully, we've left you with some fervorly thought, taking you through our journey. There's never a project of this magnitude that goes perfectly. Ours is no different. So we'd love to hear any questions that you guys have.

Sasha and I will be at the back of the room at the end of the session for additional discussion. But thanks for spending the last 46 minutes with us.

Does anyone have any of those burning questions they want answered? Do we use, like, the microphone here or do we bring a mic? This is my first speech, so I don't know how it works. It's similar to what we have for the online sessions, unless I'm mistaken. - Go. Go for it. - All right. So both you, JJ and Sasha talked about time efficiencies. And one of the things I'm wondering about, since you're dealing with all of these datasets, is when you're ingesting that data into the CDP, do you guys tend to go with batches or streaming data depending on the data source? It does depend on the data source and just the magnitude of the changes. Where we can, we go with real-time streaming because I think the results are better and the data is fresher, but there are some situations where either we can't enable streaming or the amount of data is so large we need to do it on off hours.

So in terms of batching, how do you... Since you're talking about the time component of it, and that's interesting to me. I imagine that having that data real-time is better for campaigns. When you're starting a campaign, you have that fresher data. For batching, what's your... Do you have a preference in terms of timeframe, daily, weekly? We usually do it daily. We don't necessarily have datasets that are so large where you can need to go to weekly 'cause we're really just delting in the changes from that dataset. The initial setup, obviously, takes longer. It's better for, like, a weekend.

But daily would be ideal. We'd love to have it as fresh and real-time as possible. So we really push for daily on everything that we do. - Thank you, JJ. - You bet. - Thank you too, Sasha. - Yeah. I think what I'll add as well to the last point there is just with the daily refresh, that is a substantial time improvement from where we were operating at before as well. So while sometimes the static lists... Well, potentially, with static lists and finding who to pull it from, it could take three to five days. So coming down to one was an improvement. That's a big difference. Yes. Thank you.

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