WTF ISCUSTOMERINTELLIGENCE?

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TABLE OF CONTENTS

Introduction How is itunique?

What is it? Is it really new?

The one-platformapproach

Who’s affected most?

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The silo problem The first-partybreakthrough

How is itused in thereal world?

Why now?

What comes next?

Introduction

To build direct and lasting relationships with their customers, marketers need to understand who they are, and what they want in the moment.

That’s a tall order.

Today’s customers are active across a vast array of channels and digital devices: mobile phones, tablets, voice assistants, smart watches and more. At any given moment, they could be active across an endless ecosystem of touchpoints, from websites, social platforms, and online marketplaces to brick-and-mortar stores.

All this activity across multiple devices and channels produces a whirlwind of data: product preferences, search history, purchase behavior, and much more. For marketers, that’s both a blessing and a curse.

Yes, there’s a greater wealth of customer information, but that doesn’t necessarily translate to understanding. Too much data can overwhelm the senses, clouding a marketer’s insight rather than enhancing it. Without a true understanding of their customers, marketers can’t act on their data swiftly or effectively.

To solve the problem, marketers have trundled out an array technology platforms, from CDPs, to DMPs, DSPs, CRM and more. But no matter how many acronyms they’ve thrown at the problem, marketers have succeeded only in making things even more confusing, relegating data to new technological silos rather than shedding light on it.

Before marketers can reach their customers on a personalized level, they’ll need to find out...

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Broadly speaking, the phrase “customer intelligence” refers to technology systems that analyze customer behavior to enable more effective marketing decisions. At the core of customer intelligence is the ability to aggregate customer data from a variety of disparate sources and process that data in real-time to produce actionable insights, which helps marketers make better-informed decisions about how to best engage each customer on a personal level and in a true omnichannel fashion.

What is it?

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In today’s digital ecosystem, customer activity across a multitude of touchpoints is producing more data than ever before. Marketers use this data to try and answer some crucial questions: What drove a customer to purchase? Which interaction was the driving factor that caused a customer to buy a specific item or take a specific action? How can that successful method be replicated?

Sophisticated marketers rely on a wide variety of first-, second- and third-party data: subscriber lists, website behavior, social media likes, surveys, point-of-purchase data and more. The data informs their ad targeting strategy, guiding which messages they place in front of their customers, on which channels, and when. But marketers are spreading their resources thin and, all too often, siloing their audience data among disparate technology stacks that claim to solve their every problem. Namely:

CDPs, or customer data platforms, create a database of customer information—mostly based on a company’s first-party data—with the aim of constructing profiles for individual customers. The ultimate goal is to unify disparate strands of data that are spread across other systems in an organization’s tech stack.

CRM: Customer relationship management systems analyze customers’ relationship history with a company, using that data to create customer profiles. Unlike a CDP, they’re not built to take in massive amounts of data from other tech platforms.

DMP: A data management platform is a piece of software that ingests and sorts data, which organizations can then use for ad-buying or targeting. DMPs have historically subsisted primarily on third-party data, but in a move to better compete with CDPs, they’ve begun making use of more first- and second-party data.

DFP: DoubleClick for Publishers is a Google-run platform designed to manage the process of delivering direct and programmatic ads to digital platforms.

Data Warehouse: Data warehousing is a system that aggregates structured data from one or more sources so it can be compared and analyzed.

Suffice to say, marketers have access to a vast range of data, along with the means to collect, sort and utilize it. The problem is, with so many means of collection at their disposal, their data becomes scattered and siloed across a dizzying array of technology platforms. In short: Organizations are housing their data in too many different places.

The silo problem

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The irony is, marketers implement these tools in large part because they want to break out of silos—to extract customer data from innumerable digital platforms and make sense of it all. But when marketers filter their data onto five different databases, they then become silos of their own. That exacerbates a situation where vast amounts of disparate data gets housed in different locations, leading to incomplete customer profiles and wasted time connecting the dots.

DMPs, for example, were once thought of as a surefire way to tackle the problem of siloed data. But DMPs don’t solve problems automatically. Most of the time, marketers have to stitch data from their DMPs into the rest of their ad-tech and mar-tech stacks. To try and make the most of all their data, marketers wind up with more platforms—not just a DMP, but a DSP, an attribution platform, a personalization platform, and a content optimization platform.

As a result, marketers wind up managing customer relationships in a disjointed manner without a holistic view of customers, their real-time interests, or the context of their engagement with a company’s platforms.

To make things worse, all that data winds up fragmented across numerous divisions and functions within an organization. “Often, sales applications don’t have access to marketing information,” said Sheryl Kingstone, vice president of research for the tech advisory firm 451 Research. “Marketing doesn’t have sales information, and customer service doesn’t have marketing information.”

Companies must tailor messages to individual customers across a vast collection of channels: email, display advertising, social platforms, search, and much more. But faced with an overwhelming wealth of decentralized (and often redundant) data, marketers still struggle to develop holistic a understanding of their customers’ behavior and preferences.

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Customer Intelligence PlatformGet a deeper understanding of your customers and engage them across channels including Search, Display, Social, Email, and your own website.

Understand each customer’s products of interest, path to conversion, and more.

Value each customer based on purchase intent, level of engagement, and likelihood to convert.

Engage your most valuable customers with personalized, cross-channel messaging using IgnitionOne solutions or your own technology.

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Visit www.ignitionone.com/WTFisCI to learn more

The one-platformapproach

That’s where customer intelligence comes in. It helps brands link these disparate systems and make them work better together.

“We’re seeing a lot of integration of marketing systems, which collectively are exposing a bunch of new use cases,” said Michael Horn, chief data officer at the digital agency Huge. “Segmentation and personas have been around forever. What’s different about applied customer intelligence is being able to deliver a more personalized experience for all your customers, and knowing where they are in their journey.”

Customer intelligence is about breaking down the silos—this time for real—by combining the various aspects of data management and activation. With a customer intelligence platform, data is collected from disparate sources, consolidated into customer profiles, and analyzed to unlock buying behaviors and preferences of at the individual level.

Speaking of which, one major function of customer intelligence platforms is to help marketers truly resolve the identity of individual customers. Armed with detailed and de-siloed data, an organization is better equipped to communicate directly with customers, and to make sure it’s targeting the same individual across touchpoints instead of getting mired in redundancies.

“Whether it’s something like accepting advertising in return for free content, or giving you more details about my financial situation in return for better product information, there needs to be a degree of value exchange,” said Anant Mathur, evp and head of global analytics at the digital agency Essence. “That’s rooted in your understanding of the person, and that understanding needs to be filled by a profuse understanding of customer identity across different touchpoints.”

Simply put, customer intelligence provides marketers with something elusive: a single view of the customer. By extracting actionable insights and providing that single view, customer intelligence enables marketers to execute their strategy more efficiently, without having to sort through different ranges of audience data that are situated in different technology stacks.

To be clear, customer intelligence doesn’t aim to replace those technology stacks, but to synchronize the data and enable faster and more accurate marketing decisions—for instance, which personalized messages to deliver across which channels and when; which customer interactions on which channels to attribute purchase decisions to; and which overarching KPI to measure against.

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How is it usedIn the real world?

Marketing. Marketers use customer intelligence to reach customers at the right moment, and on the right platform. A customer intelligence platform will process a variety of contextual information, such as past purchases and on-site behavior in real time, and then help marketers deliver the most relevant ad or offering in the right market at the right time.

“Insight into customer browsing behavior and on-site activity is very useful for personalization, which happens across a lot of different surfaces,” said Jeff Palmucci, director of machine intelligence at TripAdvisor. “Browsing behavior also gives rise to a bunch of collaborative filtering solutions that we put on site—for example, because you are looking at this particular hotel, you might be interested in these other ones.”

“Whenever we think about surfacing data and deriving ‘intelligence’ from our data, it’s about the actions and intents of the traveler,” added Jeff Chow, TripAdvisor’s vp of product and user experience. “Then the other side of that is mining all of the persistent data to figure out how we can actually surface the right information at the right time.”

A customer intelligence platform might also help marketers dive even deeper—for instance, targeting a traveler with personalized ads displaying the weather in their region.

E-commerce. E-commerce pros use customer intelligence to assess customers’ product interests in real-time and then make predictions. For instance, a shopper might search for several types of shoes on a department store’s website, but their purchase history and on-site behavior might determine which shoes they’re actually likely to wind up buying. E-commerce marketers can use that information to personalize on-site targeting.

Omnichannel personalization. For marketing and advertising pros, true omnichannel targeting is something of a holy grail. Customer intelligence can help marketers gain a better understanding of where and when their various customer segments are active, and on which platforms they’ll be most receptive to messaging.

Let’s say a prospective buyer is active on a car manufacturer’s website. A customer intelligence platform can help marketers assess each customer’s engagement with the website: Which specific models were they looking at? Were they reading reviews? A customer intelligence platform will ingest that information and then delegate it to the right platforms, whether that’s the manufacturer’s DSP or social media management tools. As a result, the car maker can distribute truly personalized content across the right marketing channels and at the right moment.

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How is it unique?

Marketers talk a lot about “intelligence” these days. Phrases like “marketing intelligence” and “artificial intelligence” aren’t exactly new. What sets customer intelligence apart is that it’s entirely customer-centric.

“With a customer-centric view of your category, your brand is not at the center of it,” said Michael Horn, chief data officer at the digital agency Huge. “People are interacting with a lot of other influences and competing brands and channels. A strategy with customer intelligence gives you some perspective on customers’ actual needs, and a little less of that myopic focus on just your own brand’s mission and purpose.”

Take Toyota NL, which used a customer intelligence platform to analyze online behavior of customers on their website, determining which vehicles their customers were most interested in, along with each customer’s level of engagement. Toyota used the information to create custom audiences for social media, targeting them with offers that were precisely tailored to their interests. As a result, Toyota saw dramatic spike in online clicks—nearly 90 percent—along with a corresponding 360 percent spike in conversions.

Marketers who make use of customer intelligence are able to attribute all the data they collect to singular customers, integrating that information across other ad-tech and mar-tech solutions to connect a single ID to a single customer. That enables them to arrive at a long sought-after goal: True one-to-one attribution and omnichannel personalization.

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Is itreallynew?

In short, yes. Until customer intelligence came into the picture, recent conversations in digital marketing were mostly centered on one of the above-mentioned tech stacks: customer data platforms. The problem with the CDP industry today is that it’s populated with a glut of service companies offering a confusing array of different technologies, all of them claiming to be part of the same environment.

In truth, these companies rarely speak to each other, which leads to those same old problems: Over-siloing and lack of communication. Companies and advertising technologies that purport to make marketers’ lives simpler have done the exact opposite.

“The CDPs turned out to be another silo on a marketer’s desktop,” said Kingstone at 451 Research. “So now you had silo upon silo upon silo.”

Customer intelligence has changed the game by giving more functionality and connectivity than mar-tech and CDPs have in the past. That’s because it houses real-time programmatic technology in a single location, while supporting integration with other tech firms. CDPs and mar-tech technology haven’t disappeared — but they’re working in tandem for the first time.

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Marketers can find themselves wasting time and resources if, as a result of misreading their first-party data, they mistake a single customer for two, or three, or six.

“One challenge that arises is when marketers inadvertently double-count or misattribute channels,” said Huge’s Michael Horn. “You do require some planning. What are the infrastructural elements that span channels? Where are things justifiably kept distinct?”

Customer intelligence lets marketers leverage first-party data—the data they collect directly from their audience—in a swifter and more meaningful way. In part, that’s because it allows marketers to collect such data in an organized way and act on it in real-time, without the need to filter and understand layers of information collected from numerous tech stacks.

The first-partybreakthrough

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Marketers have been overwhelmed by the growing complexity of marketing. Industries across the board have faced increasing pressure to execute a unified strategy that bears meaningful, measurable interactions with customers, and that lets them see the results in real-time. Most of them have been unable to do so. In many cases, internal communication within organizations has been severely hampered.

The retail, automotive, financial, travel and hospitality industries have been affected most. In these industries, the customer is king. A brand risks severely damaging its relationships with customers if it tries to speak to them on an individual level and says the wrong thing.

“If we want to be able to have consistent understanding of [customers],” said Horn, “we need to follow their behavior patterns.”

Indeed, it’s crucial for brands to understand their customers’ cross-channel behavior and preferences; it’s the only way to ensure that they’re having the right conversations. Loyalty isn’t what it used to be: There are too many other brands out there, and when customers think a brand doesn’t understand them, they’re quick to find one that does.

Who’saffectedmost?

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Why now?

It’s hard to arrive at a comprehensive view of the customer and gain channel-specific insights when today’s customers are active on a vast array of platforms. According to Statista, the number of connected devices per person is expected to reach 6.58 devices by 2020. That roughly indicates a jaw-dropping 50 billion connected devices worldwide.

Marketers haven’t always reacted to such a daunting media ecosystem with the right tools and strategies. Digital marketing has a reputation—not totally unwarranted—for reducing people to numbers, segments, and vaguely-defined profiles. With the number of shared devices and personal devices continuing to grow, the volume of customer data only continues to proliferate.

What we now think of as a “customer identity” is often anything but solid. And customer profiles will only continue to be diluted further as new channels and touchpoints inevitably continue to emerge. It’s no surprise that many brands are taking a shot in the dark when they try to achieve personalization.

Customer intelligence aims to turn the lights on, providing a consolidated view of customer interactions with data pulled from disparate sources. That gives marketers a clearer look at the profiles of each individual customer, along with a deeper understanding of each customer’s unique relationship with a brand.

When marketers gain that perspective, they’re able to provide customers with consistent experiences, personalizing content based on their past interactions with a brand. Leveraging that understanding is essential for marketers to cultivate that relationship and gain a lifelong customer.

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Whatcomesnext?

“I can’t think of any major sectors of the economy which are not being impacted by changes in AI and the way that we interact with our customers,” said Essence’s Anant Mathur. “So many touchpoints are moving to digital, and all of that has some element of AI behind it, in terms of predicting what a customer’s going to need next.”

Customer intelligence uses AI and machine learning to combine crucial tools such as attribution, data modeling, and personalization onto a single platform, enabling marketers to create real-time engagements on different channels. It also offers seamless integration with other third parties.

When considering the possibility of investing in a customer intelligence platform or building one internally, most companies choose the latter. But that is starting to change. For one thing, a small number of tech providers are starting to emerge in the space with more mature offerings. The next step is awareness and adoption.

“Yes, maybe you need to pull together a couple of pieces [internally],” said Kingstone. “Sometimes you want to push data into a CRM that a salesperson is already using because that’s what they use every day. But I don’t recommend building it. The way the market’s maturing, you don’t really need to do that anymore.”

Once marketers embrace customer intelligence, they’ll have a much easier time gaining a singular, comprehensive understanding of their customers on an individual level. It will be far easier to create omnichannel solutions that make targeting more accurate and efficient, moving swiftly toward true personalization.

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