How to Optimize Customer Journeys, Attribute Revenue, Create High Engagement via Lightning-Fast Analytics & Data Clean Rooms in a Post 3P-Cookie World
Consumer privacy laws such as GDPR and CCPA are slapping brands with severe penalties for violations. Violation of the law is second only to the devastating loss of consumer trust. The stakes keep getting higher.
Third-party cookies are going away, really. The clock is ticking.
Consumers demand relevance. They expect brands to know what they want, where, and when they want it while keeping brands “on a tight leash” for how their data must be used, or not be touched. The tables have turned.
COVID wreaks havoc. Brands that thrive in this pandemic have discovered success in marketing and selling directly to consumers, despite working mostly in siloed channels. Amidst the fragmentation of consumer identity, omnichannel personalization has emerged as a priority.
Digital commerce generates tons and tons of data in real-time. To perform personalization, brands need a way of tying together different pieces of the consumer identity puzzle in order to tie together all their data. And data is the key to connecting the dots, helping brands understand and optimize consumer engagement along their purchase journey.
If consumers use multiple channels to engage, research and purchase, then brands need a platform that can store all that data and tie it to each consumer’s identity precisely and securely—a data platform that can provide a single source of truth.
The convergence of these significant forces over the last 18 months is shaking up the industry, reshaping the way brands communicate and build relationships with individual consumers, harness big data and insights to act in real-time with scale and speed, and share data among different platforms to analyze customer journey and revenue attribution. These are the challenges that Jivox IQ Blaze is designed to solve. Joining me in this conversation to share the “what, why, and how” is our CEO, Diaz Nesamoney.
Anna: There is a buzz about Jivox IQ Blaze. What is it?
Diaz: Jivox IQ Blaze is the new technology upgrade to the Jivox omnichannel personalization platform. We have been working on it for a little over a year. Essentially, it is about upgrading the data and analytics capabilities of our platform. As most of our customers know, data and analytics are incredibly important for personalization. The reason is data is the fuel for personalization. The more data and the more precise the data, the better the personalization. Secondly, data is also important from these campaigns to optimize and improve the performance of engaging with consumers.
Anna: Okay. Here is an obvious question. Why is it relevant to the digital marketing industry as a whole?
Diaz: It is quite relevant because the amount of data that’s generated is tremendous, both in terms of consumer engagement and all of the different activities that consumers undertake on their journey to purchasing a product. All of that data is available. Then, to really optimize consumer experiences, the feedback that comes from the consumers in the form of engagement, helps a brand understand how best to engage with them and how to optimize content and create it for them. Essentially, both improve the user experience as well as the outcomes for the brand in terms of sales.
Anna: Yes, speaking of benefits, what do you say to programmatic media leaders?
Diaz: For programmatic media leaders, I think, ultimately, the metrics are all about campaign performance. If you ask a brand what they are looking for, they may say branding, engagement upper funnel, lower funnel, and so on. But ultimately, they mean sales and performance. The more a personalization platform is able to use data at scale, and the more it’s able to process the data well and to use it to optimize consumer engagement, the better media will perform. The better the media performs, the better the brand does. I think ultimately, data and analytics, being scalable, within the personalization platform are incredibly important.
Anna: What’s in it for digital marketers?
Diaz: For marketers, ultimately, it is about intelligently engaging with consumers. Not having enough data means that the personalization is poor and consumers will get put off by just bombarding them with irrelevant content and ads. The precision of the data is really important. The more precise the data, the better personalization works. Then, of course, improving campaign performance has to do with getting that feedback, that constant feedback from the consumers through clicks or other interactions. Now, the more precisely you measure feedback, the more data you get in return. Again, scale is really important in being able to process all of that data, and use sophisticated optimization algorithms to essentially improve consumer outcomes.
Anna: These days, we are seeing an increasingly strong in-housing trend. What would martech leaders and info security leaders gain from this?
Diaz: Yes. As part of this offering, one of the things that we looked at very carefully is data privacy and security because, currently and in the future, any kind of data you collect from a consumer or use for personalization has to have consent. First and foremost, the collection of the data, the storage of the data, and how data is used all have to be very secure. This ensures trust is not broken—where the consumer is providing the brand with data to use for personalization. It’s the brand’s responsibility to use it exactly and only for that purpose, and to safeguard it from falling into the wrong hands. From a data security standpoint, we put a lot of thought into this to make sure that the way the data is stored, retrieved, used, and structured all preserve consumer privacy.
Anna: Great. Since the onset of the COVID pandemic, we have been seeing accelerated growth in digital commerce and eCommerce marketing. How do eCommerce marketers benefit from this?
Diaz: eCommerce marketing, first off, works with a lot of data. Most eCommerce marketers deal with lots and lots of different products, offers, packaging of the product, and so on. It just means a lot of content, a lot of ad variations, and consumer data that’s created through engagement. Ultimately, for eCommerce in particular, you’re optimizing for conversions and sales, which means you need very granular data and to be able to process significant amounts of data with a lot of speed. Because with eCommerce, a consumer may be in the market just for a few hours or maybe even a few minutes. It doesn’t help that you process the data over a few days or weeks because by that time the consumer has completed the purchase. Doing it in real-time, doing it at scale, and doing it with a sense of immediacy is what produces the best outcomes.
Anna: What pain points does Blaze address? For example: would you say most of the analytics today are still very much a batch process and so this is where Blaze shines?
Diaz: Yes. A lot of the data and analytics infrastructure that’s used today was designed maybe 15 to 20 years ago when you had very episodic campaigns versus always-on. You didn’t get immediate consumer feedback. For example, for attribution, you often had to wait a month or so to get store sales data uploaded into your data warehouse and do the analysis. That was okay then—because you didn’t have the ability to immediately act upon any piece of data you got.
Fast-forward to where you are today when a consumer might see an ad for a product. She immediately goes to the site and wants to purchase it, or goes to the competitor’s site to purchase. Here are very, very narrow windows of opportunity to re-engage the consumer and maybe present them with a special offer or at least a relevant product. So, the old way of processing data — which is very batch-oriented — simply doesn’t work anymore. Today, it’s all about real-time, and we are talking about very large amounts of data sets, so it’s both scale and speed coming together.
Anna: Another pain point brands have to deal with is that far more campaigns are still running in silos—different channels in silos. That obviously poses a challenge to attribution. How does Blaze address that?
Diaz: Yeah. With the third-party cookies going away, the industry has, in many ways, gained from it because there are much more robust identity mechanisms coming into play. But, the industry has also “lost” in the sense that there is no single point of control for identity. That fragmentation of identity means that you have to be able to tie all of these engagements across different channels and so on together. Having the ability to tie identities is key to being able to essentially tie the data together. Knowing that consumers often use multiple channels to engage, research, and ultimately purchase, the data platform has to be able to store all of that data and tie it to identity securely in order to understand and optimize engagement with the consumer.
Anna: Excellent. You’ve talked about data security, different kinds of data, real-time, actionable insights, first-party identity in the context of Blaze. What is your message to the CMOs?
Diaz: First off, let me talk about what Blaze really is. There are two parts to Blaze. One is Blaze High-Performance Analytics, which is essentially a very scalable and high-speed analytics platform. What that allows brands to do is to be able to process large amounts of data at a significant scale and speed. It uses scalable cloud technology to process the data within a few milliseconds, really, from the time a consumer engagement happens and makes it available for optimization.
The second part is data clean rooms. These allow, for example, a brand’s data to be combined with different data from other platforms (such as attribution platforms) in a secure way so that conversions and other engagements across channels can also be done in a secure and privacy-compliant manner. These two capabilities in combination are incredibly important to brands and especially C-level executives of brands because they have been trying for quite some time to connect all of the different consumer engagement channels together to provide to individual consumers personalized experiences. To do that, you need both high-performance analytics and data clean rooms. You need both a way to analyze and process the data at scale, and also to connect it with other platforms that they may be using that are also engaging with those consumers, and ultimately to be able to tie all of those customer journeys together.
Anna: In this announcement, we specifically focus on our integration with Snowflake. Can you expand on that?
Diaz: Yeah. Snowflake’s technology is essentially what we use to enable the Blaze offering in a couple of different ways. One is the data storage and data warehousing mechanism to be able to store large amounts of data and to operate on a cloud-scale. What I mean by that is traditionally a data warehouse would have a single system in which it resided. The speed at which you could process data, the speed at which you could query data and get results back, depended on the processing power of that signal system. With Snowflake, we are able to distribute it in the cloud across many, many different servers. There is almost unlimited scale, both in terms of how much data it can process, but also the speed at which you can analyze the data and the query performance. You can have many, many, many different applications or users hitting on the data and yet deliver the analytics in split second. This infrastructure built on Snowflake is the key. This infrastructure also allows the sharing of data with other systems. The Snowflake technology allows us to do that sharing also much more easily than we have been able to do in the past.
Anna: Let’s talk about the Blaze High-Performance Analytics. What events does Jivox track?
Diaz: Just about everything. Every consumer interaction with the ads that we deliver, the content we deliver, engagement with the brand’s website, and really try to collect as much data as possible. Previously, that data had to be put in many different stores and then aggregated or moved around to essentially perform the analytics. Now, we are able to feed all the data into a single cloud data warehouse, which means we can do all the analytics in one place. Our platform can pull data and provide insights very quickly because all that data is in one place.
Anna: Data clean rooms: Could you talk more specifically about how the data flow works with Jivox, the brand’s data, and also the brand affiliates’ data? How does that all come together?
Diaz: Data clean rooms have become incredibly important for brands. The reason is primarily because of the loss of the third-party cookie that traditionally has made attribution relatively easy. Even across systems, there were ways to synchronize cookies across platforms and so you could relatively easily do that. With third-party cookies going away, the only way to enable attribution is that different data platforms and ad platforms have a secure way to share data, and essentially connect the dots to determine the attribution.
But sharing data comes with its own perils. Because now, first of all, to do attribution itself, you need very detailed impression-level data and user-level data. That is a lot of data. For example, it’s not just data out of one campaign platform, but imagine: did this particular consumer see this particular message and then purchase by acting on this particular offer? Lots of data. Very granular data. You can easily see scale as the issue.
Second, how do you share that data or combine that with other data while maintaining privacy controls? Because there are some parties that shouldn’t be seeing data about the consumer and yet you have to match up the data across different platforms. That’s essentially what a data clean room accomplishes. It allows two or more parties to put their data in one place. Neither party can see the other party’s data, but it allows certain questions like “did a conversion occur” to be answered in a privacy-compliant manner.
Anna: With Blaze, how does Jivox stack up against other players in the DCO space?
Diaz: IQ Blaze is a very significant technological leap that Jivox has made over our competitors. Most of the systems and platforms that exist out there are designed and built many, many years ago. Back then, it was perfectly fine to treat the idea of analytics, attribution, and so on as a batch process. You often had to wait several days for that data to arrive and then you had to combine it with other data. Often the resulting analytics were incorrect because of the manual process in tying the data together.
With Jivox IQ Blaze, it is completely automated. The process by which an event gets from a user interaction to an analytics report is completely seamless. The data hardly moves from where it’s collected to where it’s actually analyzed and is available within a few milliseconds for analysis. That is the state of the art.
With third-party cookies going away, there is simply no other way to do the kind of sophisticated attribution that is needed across systems without this kind of infrastructure in place that also takes care of identity and privacy as data is integrated across systems.
Anna: One final question. Is it accurate to say that, today, the majority of the brands are still seeking to put their process together in order to go where they need to be? What would you advise brands—starting at the fairly early stage of their personalization journey. How will they achieve omnichannel personalization?
Diaz: If you ask a brand or a CMO what some of the top initiatives are for the brand, personalization ranks pretty high. If not #1, it’s probably within the top 5. But to get to omnichannel personalization, data is the ticket.
Now, the good news is most brands are thinking in terms of the data infrastructure. That involves implementing customer data platforms alongside personalization platforms that are very data capable. Because without good data, brands at best have personalization that doesn’t perform. Because if the data is not very precise, and the attribution is not clear, you won’t know whether the money you’re spending on media is being effective or not.
But there is also the privacy and data security issue. I think the environment and consumers are very, very, very privacy-focused. While consumers appreciate and value personalization, they also expect brands to safeguard their data. Data infrastructure is incredibly important. Brands are implementing their own data infrastructure. But as they implement a personalization platform, they have to pick platforms that actually take data seriously, can scale with the data demands they have, both in terms of data coming into the system for personalization, as well as the optimization and attribution that comes out of the platform.
Today, Jivox already processes on average more than 2 billion events daily. To learn more about Jivox IQ Blaze and questions customers ask, please visit the blog post entitled How Fast, Real-Time And Privacy-First Analytics Can Power Successful Personalization Strategies.
To book time with one of our personalization experts and chat about your next step in the personalization journey, please let us know how best to contact you.