#606: Connecting experimentation to business outcomes across the journey with Vijay Ganesan, Optimizely

Summary

Episode #606: Connecting Experimentation to Business Outcomes Across the Journey with Vijay Ganesan, Optimizely

Release Date: November 25, 2024

Introduction

In episode #606 of The Agile Brand™ with Greg Kihlström, host Greg Kilstrom delves into the intricate relationship between marketing experimentation and tangible business outcomes. The episode features Vijay Ganesan, the co-founder and CEO of Netspring, recently acquired by Optimizely. Together, they explore how integrating advanced analytics with robust experimentation platforms can revolutionize marketing strategies and drive significant business growth.

Guest Introduction and Netspring's Journey

Vijay Ganesan begins by providing a comprehensive overview of Netspring's evolution. "[...] we were an early stage Silicon Valley startup focused on data analytics [...]" ([01:41]). He explains that Netspring was founded to address the growing need for next-generation analytics platforms centered around event data—information derived from digital platforms, websites, apps, and other digital properties. This focus allows for a more nuanced understanding of user interactions and behaviors, setting the stage for deeper business insights.

Integrating Netspring with Optimizely's Experimentation Capabilities

Greg introduces the core topic by highlighting the synergy between Netspring's warehouse-native analytics and Optimizely's experimentation tools. "[...] pairing that with Optimizely's experimentation capabilities makes this combination so powerful for marketers" ([03:06]). Vijay elaborates on this synergy, stating, "We're making experimentation more business impactful, more tied to business outcomes by accessing rich business context from the data warehouse and bringing it to the world of stats and experimentation" ([04:12]).

Benefits for Marketers: Enhanced Data-Driven Decisions

The integration offers marketers unprecedented capabilities to test their hypotheses against meaningful metrics. Vijay emphasizes the importance of moving beyond superficial metrics, such as button clicks, to more substantive business indicators like subscription revenue. "We help marketers close and accelerate these growth loops by providing self-service access to data without relying on data teams for reports" ([05:47]). This empowers marketing teams to iterate rapidly and make informed decisions that directly impact business growth.

Data Democratization and Building Trust in Data

A significant portion of the conversation centers on democratizing data within organizations. Greg points out the common challenges marketers face, including time delays and data fragmentation. Vijay responds by highlighting the critical role of trust in data: "If you cannot trust the data, you cannot take actions on it. Trust is critical" ([11:51]). By centralizing data access and ensuring data integrity, marketers can confidently leverage data to drive strategic initiatives.

Addressing Data Duplication and Governance Challenges

Vijay discusses the pervasive issue of data duplication in enterprises and its associated costs. "Data duplication leads to challenges in managing pipelines, security, privacy, and governance, especially with regulations like GDPR" ([12:34]). By utilizing a centralized data warehouse approach, the integration with Optimizely eliminates redundant data copies, reduces management overhead, and ensures compliance with data governance standards.

Advice for Organizations: Embracing Centralized Data and Self-Service Tools

When advising organizations on adopting these advanced analytics and experimentation integrations, Vijay recommends embracing centralized data warehousing and leveraging self-service analytics tools. "Embrace the new paradigm of your central data warehouse being the source of truth and connect with your data teams. Look for systems like Netspring that provide self-service access to this data" ([14:00]). This approach fosters a more efficient and collaborative environment between marketing and data teams, enhancing overall productivity and ROI.

Collaboration Between Data Teams and Marketers: A Symbiotic Relationship

Greg and Vijay explore the collaborative dynamic between data teams and marketers. Vijay introduces the concept of "governed self-service," where data teams maintain control over data access while marketers gain the autonomy to analyze and act on data independently. "Data teams can control who gets access to what in the data warehouse, ensuring security and governance, while marketers can self-serve without constant report requests" ([15:58]). This balanced approach ensures data integrity and fosters a productive partnership between departments.

Staying Agile: Continuous Customer Engagement and Iteration

Towards the end of the episode, Greg asks Vijay about maintaining agility in a rapidly evolving market. Vijay attributes this agility to consistent customer engagement: "You have to be talking to the users of your product every single day and learning from it and constantly iterating" ([17:36]). This customer-centric approach ensures that products and strategies remain relevant and adaptive to changing market needs.

Conclusion

Episode #606 of The Agile Brand™ underscores the importance of integrating advanced analytics with experimentation platforms to drive meaningful business outcomes. Through the insights shared by Vijay Ganesan, listeners gain a clear understanding of how centralized data access, self-service analytics, and collaborative dynamics between data and marketing teams can transform marketing strategies. By fostering trust in data and emphasizing continuous customer engagement, organizations can achieve greater agility and significantly enhance their return on investment.

Notable Quotes

• Vijay Ganesan on experimentation impact: "We're making experimentation more business impactful, more tied to business outcomes by accessing rich business context from the data warehouse and bringing it to the world of stats and experimentation." ([04:12])

• Vijay Ganesan on data trust: "If you cannot trust the data, you cannot take actions on it. Trust is critical." ([11:51])

• Vijay Ganesan on governed self-service: "Data teams can control who gets access to what in the data warehouse, ensuring security and governance, while marketers can self-serve without constant report requests." ([15:58])

• Vijay Ganesan on staying agile: "You have to be talking to the users of your product every single day and learning from it and constantly iterating." ([17:36])

This episode is a must-listen for marketers and data professionals aiming to harness the full potential of their data to drive business success.

Transcript

[Vijay Ganessan]

The Agile Brand.

[Greg Kilstrom]

Welcome to Season six of the Agile Brand where we discuss marketing, technology and customer experience, trends, insights and ideas with enterprise and technology platform leaders. We focus on the people, processes, data and platforms that make brands successful, scalable, customer focused and sustainable. This is what makes an agile brand. I'm your host Greg Kilstrom, advising Fortune 1000 brands on martech, marketing operations and CX best selling Author and speaker. The Agile Brand Podcast is brought to you by Tech Systems, an industry leader in full stack technology services, talent services and real world application. For more information go to teksystems.com now let's get on to the show.

How do you know if your marketing efforts are actually driving real business outcomes? Imagine being able to tie every experiment, campaign and variant to metrics that truly matter. I'm here at Opticon 2024 in San Antonio, Texas and getting the opportunity to see a lot of inspiring ideas from some of the world's leading brands and hearing all about optimizely's platform and how it enables one to one personalization, streamlined content operations and incorporates the latest generative AI features. Today we're exploring the power of connecting marketing and experimentation to business outcomes with Vijay Ganessan, co founder and CEO of netspring, now part of optimizely. Vijay, welcome to the show and congrats on the acquisition. Why don't you start by telling us a little bit about yourself and your current role.

[Vijay Ganessan]

Great. Thank you Greg. Great to be on your show. Excited to be part of optimizely. Optimizely acquired us just about a month ago. Netspring we were an early stage Silicon Valley startup focused on data analytics and our history. The genesis of netspring. We started the company with this realization that there is a market need for next generation analytics platform that's focused on what we call event data. This is data coming from your digital platforms, instrumentation of your websites and apps and other digital properties. And so we recognize that there was an opportunity to build a more powerful platform there and that's a journey we embarked on and we're glad to be part of optimizely now. Scale it to thousands of customers.

[Greg Kilstrom]

Love it. Yeah, well, so yeah, let's dive in here. So we're going to talk about a few different aspects of just how this integration can be valuable. And so the first thing that I wanted to talk about is experimentation capabilities. So you know, netspring brings these warehouse native analytics to the table. So now pairing that with optimizely's experimentation capabilities, you know what makes this combination so powerful for marketers.

[Vijay Ganessan]

Yeah. So if you look at how experimentation is done today, whether it's optimizely or whether other systems, they're done in these fairly siloed systems where you measure the effectiveness of experiments based on sort of first level of impact. Right. So for example, you ran an experiment and you're measuring how many people clicked on a button. Right. But to make the analysis more business impactful and tied to business outcomes, you need to go to the next levels of impact rate. So for example, you may want to understand the impact of an experiment on subscription revenue, for example. And a lot of the data is not in these experimentation systems. They're sitting outside in the data warehouse. And so the problem we're solving here is we're making experimentation more business impactful, more tied to business outcomes. And the way we're doing it is being able to easily access this rich business context that is sitting in the data warehouse, bringing it to the world of stats and experimentation.

[Greg Kilstrom]

So what does that mean from the marketers perspective? So optimize League 1 is it's a marketing operating system and so marketers doing a lot of different things in that. What does this kind of integration mean for companies looking to innovate in this marketing?

[Vijay Ganessan]

Yeah, so we're starting out with experimentation. That's the first integration we're doing with Optimizely. But our vision is to make Netspring analytics pervasive across all aspects of Optimizely 1. If you think about very successful marketing organizations out there, the one characteristic you'll see of all of them is they're very, very data driven in everything that they do, whether it's in the CMS side, the CMP side, experimentation side, personalization. They're very, very data driven. And so that's what we bring to the table with Optimizely 1. Netspring analytics is going to become a common substrate across everything that a marketer does with an optimizely one.

[Greg Kilstrom]

Got it, Got it. So you know, benefits of this integration include the ability to test against metrics that matter. As you were mentioning, you know, in the e commerce space this might be like return adjusted revenue. You know, those things that to your earlier point are they're not necessarily available in a lot of platforms. Direct. Right. They're one or sometimes a few steps removed. What do marketers get to do differently when they have access to the like, what can they do better?

[Vijay Ganessan]

Yeah, so a lot of what people do in marketing is very hypothesis driven. Right. You know, you have a hypothesis about influencing user behavior typically. And you're testing that hypothesis. And one of the things that make for effective marketing is to be able to close these, what I call these growth loops. You start an initiative, you launch it, you test it, you iterate on it. And there are these growth loops. And so what we help marketers do is to first of all close the loop. So to close the loop you need access to data that you typically don't have access to. And that's the warehouse native aspect of it. And then the second thing is you need to accelerate this closing because if it takes a month for you to close a loop for a certain hypothesis you're testing, it's too late, the market's moved on. That acceleration we provide with our product which has a very self service interface for marketers that they don't have to wait around for their data teams to come up with a report three weeks later they can self serve through our self service interface. So that's the essence of what we help marketers do with the Optimizely one and netspring integration. We help you close and accelerate these growth loops.

[Greg Kilstrom]

Yeah, and to that point about speed to insights or those closed loops, Netspring integrates with platforms like Snowflake, BigQuery, places that are already being warehouses that are already being used by these companies. So it doesn't, I think to your point, this is instead of sending a request out and waiting weeks. And then I've seen this before, you know, a marketing team, they wait for the data and then it takes them time to analyze the data and then it takes them time to act on the data. So you know, they're like two months out from being able to act. So you know, how does, how does integration with some of these known or you know, currently used platforms improve flexibility as well as data integrity.

[Vijay Ganessan]

Yeah, so great point. So if you look at what's happening today, what you said about the snowflakes and the big queries of the world, clearly the center of gravity of data is the data data warehouse. And it's not just business transactions. Data coming from your sales force and Zendesk event data is coming to the data warehouse. Your product instrumentation data is your website. Instrumentation is flowing into the snowflakes and big queries of the world. So that is the undisputed center of gravity of data in the enterprise. The way marketers have been operating is they've got these purpose built tools that they do some things they get some insights from and then like you said, for the rest of it they're waiting around for their data teams to produce a report, which is the time it takes to get that is a problem. But the other problem is you get that results in a disconnected form, you get it in another tool, you get a BI report from. Now how do you integrate these two? The analysis you're doing in your purpose build tool and the BI report that you're getting from your data teams. You cannot connect them, right. And so analysis becomes very fragmented in two separate tools. You cannot share context across them. And so it just becomes the ROI diminishes and you stop doing a lot of this additional analysis that you try to do. Right. So what we're trying to do is to bring all of that into a single tool working off the single source of truth, which is the data warehouse. And so that simplifies the experience quite radically for the marketer. And then on top of that, when you make it self service for the marketer for a majority of what they need, they can just get it themselves without having to call their data teams marketers.

[Greg Kilstrom]

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And so to kind of dive into that a little bit more, this idea of democratizing data, I think there's quite a bit of talk about that but in practice it involves things like what you're talking about, it involves that connection and I think you touched on a few kind of challenges. When that doesn't happen is, you know first the time aspect that we talked about, then the disconnect of, you know, they get one report and they have to tie it to another report. And, you know, there's not only room for potential misinterpretation or, you know, or things like that, but can you talk a little bit more about what do marketers get to spend more time on, I guess when they're not trying to correlate things that, you know, are difficult to do and, you know, what does that mean for the marketers?

[Vijay Ganessan]

I think the biggest thing it means is trust. So if you think about it, yes, you want to close the loop, you want accelerate and all that, but end of the day, if you cannot trust the data, you cannot take actions on it. You won't take actions on the data if you don't trust it. So trust is critical. And so what this lets marketers do is to be able to trust the data enough to be able to take bold decisions based on the data.

[Greg Kilstrom]

Yeah, yeah. And, you know, there's also data duplication and you know, there's, there's a lot of other things that this also helps to eliminate. Can you talk about, you know, what are the, you know, costs, so to speak, of doing that?

[Vijay Ganessan]

Yeah. So, you know, data duplication is the biggest challenge in enterprises. And anytime a copy of the data is made, it, it results in lots of challenges. Managing the pipelines to move data across different systems. Security, privacy, governance challenges, especially when data goes outside of your central systems to some black hole somewhere. Things like GDPR and all that are important. So there's the cost aspect because these get expensive. Every pipeline you add, every new system that you add introduces cost both in terms of managing these pipelines, in terms of paying for duplicate copies of the data, and then all the governance security challenges that it imposes. So there's a lot of challenges with traditional systems and we're solving a whole bunch of problems with this approach where we say there's one place where your data lives and no copies are made and we work directly off that data with an interface that is, that is very easy for a marketeer.

[Greg Kilstrom]

Yeah, yeah. So what advice would you give to organizations that, you know, maybe not quite here yet, you know, but wanting to move in this direction, you know, giving greater democratization, you know, tying things more closely to business outcomes, you know, where should they start?

[Vijay Ganessan]

Yeah, I'd say, you know, embrace your data teams or the centralized data warehouse teams. If you look at how, say, CDPs evolve, one of the primary drivers for CDPs was marketers wanting to be self sufficient. That I don't want to deal with decentralized data teams and I've got my own world of customer data in a platform that's sitting outside of the enterprise and that's resulted in a lot of mess with a lot of duplication of data and so on. So my advice would be embrace this new paradigm of your central data warehouse being the source of truth and get connected with the data teams and then look for systems like netspring that give you the ability to access the data very easily, that not only do you have access to that single source of truth, but you can access it in a self service fashion and be self sufficient for a lot of things that you can do. And then the final thing I'll say is, and this is the crux of this acquisition and the value we bring to Optimizely one is this idea that you can really make your digital experience initiatives more business impactful and that's really the crux of growth in your business. And so you really can take analytics to the next level. You can get an order of magnitude increase in the ROI of your digital experience initiatives.

[Greg Kilstrom]

Well, and I want to dive into one quickly. One, one thing that you touched on too, which is at least from, from what I'm hearing, this also helps. You know, I work with marketers a lot. I also work with data teams a lot. And it, there's a, there's a strong role for each of those teams in, you know, it's not like all of the stuff is given to marketers and then you don't need data, you know, you need both. But it actually, it seems like it focuses each on what they really need to do. Is that.

[Vijay Ganessan]

Yeah, absolutely. So this actually the data teams have an important role to play too and data teams love us because what we help them do is what we call a governed self service. So self service can be challenging in environments where everyone's going and creating their own interpretation of the data. So govern self service is the key. So what our architecture allows data teams to do is to control who gets access to what in the data warehouse. So they control the central data warehouse, they expose certain aspects of the data to certain teams as appropriate. They can audit all access, they can model the data in a fashion that is amenable for self service. So it's really a very symbiotic relationship and it's a win win for both teams because the data teams have comfort in knowing that everybody's working off the single source of truth and everybody's only accessing the data that they're supposed to access. And then at the same time they can let the marketing team self serve and not have to bother them with repeated requests for reports. And then finally, even if there are some elements where you go to your data team to build some more complex stuff, both these groups are working in the same tool. These are not separate tools. So they're all working collaboratively in a single tool.

[Greg Kilstrom]

Yeah, yeah. That's what I call a win win. Right. So that's, that's great. Well, one last question for you here. I really appreciate talking with you today and this is something I ask all my guests here. What do you do to stay agile in your role and how do you find a way to do it consistently?

[Vijay Ganessan]

Yeah, great question. If you're in a product oriented company, you're building software, you're building products. The number one thing that I think I do to stay agile is to talk to customers all the time. You have to be talking to the users of your product every single day and learning from it and constantly iterating and that's the, that's the way to be agile.

[Greg Kilstrom]

Yeah. I love it. Love it. Yeah. I learned something from every conversation I have. So it's. I can, I can see. That's great. Well, again I'd like to thank Vijay Ganesson, co founder and CEO of netspring, now part of Optimizely, for joining us today. You can learn more about Vijay, netspring and Optimizely by following the links in the show notes.

Thanks again for listening to the Agile brand brought to you by Tech Systems. If you enjoyed the show, please take a minute to subscribe and leave us a rating so that others can find the show more easily. You can access more episodes of the show at www.gregkilstrom.com. that's G R E G K I H L S t r o m.com While you're there, check out my series of best selling agile brand guides covering a wide variety of marketing technology topics. Or you can search for Greg Kilstrom on Amazon. The Agile Brand is produced by Missing Link, a Latina owned, strategy driven, creatively fueled production co op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. Until next time, stay Agile.

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