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Customer Data Platform: What It Is and Why Marketers Need One

March 17, 2021

customer-data-platform

Data, data everywhere – but where do marketers begin?

Imagine you’re a tourist and you find yourself in a foreign country. How do you navigate yourself within the region?

The obvious answer to this dilemma is to use a map, of course.

What if your map only had coordinates to certain locations, but no names? Can you still find your destination?

The problem here isn't that you don’t have any data. On the contrary, you have an abundance of data in your hands, but you just don’t know how to make sense of it. 

There was a time when marketing teams were hard pressed to find quantifiable data. Today, businesses have an overwhelming amount of data at their disposal, itching to be analyzed and used. 

Marketers don’t have an issue with the amount of data that’s lying there; however, extracting value out of the data seems to present some hiccups. 

Marketing teams have access to social media analytics, behavioral data, click rates, market intelligence, and so much more. There are tons of software tools today that cater to capturing and analyzing different sets of data. Data obtained from these channels however, is often treated as standalone. How do marketers combine discrete sets of data to obtain a single customer view?

If only there were a single unified customer database that captured data from various sources and channels and provided actionable insights on a customer at different touch points within a customer journey.

There are platforms like this. They’re called customer data platforms.

Why do you need to know about CDPs?

CDPs are the newest residents of the marketing technology (martech) neighborhood. You’re probably thinking, “Another martech tool? I’ll pass.” And you might even be justified for thinking that way considering that there are thousands of martech solutions available today. 

24.5%

was the rate by which the martech landscape grew in 2019.

Source: chiefmartec.com

But CDPs aren’t the same thing as a marketing automation tool or a CRM. They may all be martech tools, but they each have very specific functionalities. Having one does not substitute for another by any means. 

Think of it as spoons and knives – they’re both cutlery, but you can only drink soup out of one of them.

How does a CDP work?

Gone are the days, where a customer’s journey was as simple as someone walking into a store and making a purchase. Technology has blessed consumers and businesses alike with omnichannel experiences. While omnichannel strategies have eradicated the issue of customer reach, a new problem presents itself. 

Definition: An omnichannel experience aims at bringing the business to the customer seamlessly across a multitude of mediums. Omnichannel strategies integrate online and offline channels to establish an interaction with the customer.

Customer journeys aren’t tidy, straight lines that culminate in just a few steps. Today, a  customer journey could start from any source and can toggle between several steps over a period of time. With every interaction a customer has with a business across the customer lifecycle, data is produced. 

Let’s take a look at a general marketing campaign for lead generation purposes. 

Your marketing team will try to cover all their bases and launch myriad targeted ads across social media, send out emails, and create content around the campaign. Any campaign that is executed is typically a mix of organic and paid efforts.

Toward the end of the campaign, you would’ve evaluated its performance and the leads that have been generated. All the leads from email campaigns, social media ads, landing pages, and the website are compiled and put in a common database, (likely a CRM). 

Mission accomplished, right?

If you think the end goal of any marketing campaign is to just generate marketing qualified leads (or MQLs) and push the list to your sales team, you might want to re-evaluate the way you look at your marketing efforts.

Human behavior dictates the way someone reacts to a campaign. Customers that are swayed by the first CTA button they see is something we’d all like to achieve, but quite obviously isn’t the standard reality. 

Studying customer behavior can help you draw conclusions about what clicks with them, and what in turn makes them click on the CTAs. This is where a CDP comes into play.

how cdp works

Data collection

CDPs, as the name suggests, deal with everything that has to do with customer data. There are multiple streams of data that are created when a channel is exposed to any customer interaction. Based on the type of data and its origin, these streams reside across disparate platforms and systems. 

Tech-savvy marketers are already acquainted with several tools and analytics. As mentioned earlier, today’s marketers have a host of tools and platforms that steadily aggregate data of all types. 

All these platforms don’t automatically share this data with other tools unless you plug in an integration to do so. So now you’re left with a bunch of data that’s siloed across multiple platforms. Drawing conclusions from data would require checking each platform individually and comparing them with other platforms.

To put things into perspective, would you rather collect a glass of water from every house in a suburb to fill up a pool? Or would you rather use a hose connected to a centralized water supply?

Now imagine if the data from all these platforms and tools were consolidated into one giant tank. 

This is the first step that a CDP does: collect and consolidate data onto one unified platform. Now you have a complete picture as opposed to breadcrumbs scattered across a hub of marketing systems.

Data analysis and profile creation

After all the data is centralized across a single platform, the next step is to read and analyze this data.

Customers don’t like to be seen as customers. They want to be seen as individuals and not as a hit on a website. It can get hard for marketers to view people as such considering the data that flows in, making prospects look like a cell on an Excel sheet.

Every type of data that is collected serves a purpose. Put together, data can paint the picture of a profile or a persona. CDPs have the distinction of creating unique and comprehensive profiles.

The data collected is first cleaned and deduplicated. Next, similar datasets for a particular customer are grouped together. This data is used to generate a unified customer profile that includes descriptive details such as their identity, their behavior, their likes and dislikes, and their perception about the businesses they interact with.

Considering the amount of data that is collected by the CDP, it’s not surprising that these profiles are extremely detailed. You can glean more information from profiles like these than from identity information and contact details that would be captured from a landing page. 

Segmenting profiles

While each customer is an individual that acts and behaves a certain way, there are times when a few customers exhibit common patterns. 

For example, people belonging to a certain demographic relate to messages differently. Millennials prefer messaging that is more casual and current. Baby boomers probably wouldn’t appreciate memes as a form of communication.

From the profiles that were created earlier, CDPs can match profiles that exhibit some alignment based on the data that already exists on the platform. By segmenting customer profiles, marketers can hyper-personalize messages and ads to the right set of people.

Generally, a CDP can exhibit the following functionalities:

  • Collect, clean, standardize, and authenticate data captured across disparate martech tools and systems, onto a unified platform.
  • Match relevant data from different sources to create a comprehensive customer profile and provide a 360-degree view of the customer.
  • Feed these profiles of their target audience to other tools to push tailored messages.

How is a CDP different from a CRM?

If CDPs and CRMs were related, they wouldn’t be siblings. They might be distant cousins, if you will. 

By now, you must’ve seen the term ‘customer data’ mentioned several times. There’s been a lot of talk about data and how CDPs collect it for further customer data analysis

You might be wondering, “What’s all the hullabaloo about these CDPs? Don’t customer relationship management tools (CRMs) do the same thing?”

The short answer? No.

The slightly longer answer? CRMs contain data you already know while CDPs collect data you wouldn’t know over a period of time.

It’s time to break down the differences between a CDP and a CRM.

To be clear, CRMs and CDPs do have a few things in common: they both collect and analyze data. The difference really lies in the kind of data these tools collect. 

CRMs were intended to keep track of interactions with prospects and existing customers, and automate the entire sales process for business development teams. They’re a great tool for sales and marketing teams alike, especially if anyone wants to quickly pull out information on the customer.

CRMs were not designed to handle copious amounts of data from various sources however. 

The data you store on a CRM are neatly packaged into a few fields. Think of it as a flashcard for folks that want to know basic details like a customer’s name, designation, and contact information. Information about a customer’s buying patterns, hashtags a user might be following, or their online activity have no place in a CRM. 

Probably the biggest distinction between a CRM and a CDP is the fact that CRMs only contain known data. 

You will find information on existing customers or prospects that are currently somewhere within the funnel. CRMs will not be able to pull out data on potential customers you’ve never even met before. CDPs have an edge over most martech tools considering they can work with both known and unknown data. 

Feeding data on a CRM needs to be done beforehand via CSV files or Excel spreadsheets since CRMs aren’t equipped to handle data in a free-flowing manner. Data can only be recognized by the system if it is formatted a specific way.

CDPs on the other hand, are built to take in data from several sources and are meant to act as a central repository of sorts. They are equipped to handle not only identity data like contact information, they can take in, and make sense of other types of data like online and offline data as well as behavioral data.

cdp-vs-crm

This isn’t to say that CRMs are redundant and don’t contain relevant information. CRMs are great at monitoring and engaging with prospects across all stages of the customer cycle. They’re excellent contact management tools, have provisions for automated workflows, and provide timely reports on deal closures as well. 

It’s simply a matter of what you may need to accomplish when, and with which tool.

How is a CDP different from a DMP?

On the other side of the spectrum, we have data management platforms (DMPs).

While CRMs are incapable of capturing and analyzing data of people you don’t know, DMPs can collect unstructured data across a host of sources and mediums. Sounds pretty similar to our buddy CDP here, doesn’t it?

DMPs have traditionally been known as a component of adtech. They rely on third-party data like cookies to facilitate retargeting advertising efforts. However, this aggregated data cannot point to individual customers since it focuses on anonymous segments. 

Third-party data makes it easy for businesses on social media pages like Facebook and Instagram to retarget ads to these anonymous segments. That doesn’t always mean people in these segments are looking for something to buy.

Let’s say someone clicked on an Instagram ad for custom pet accessories. This person doesn’t even own a pet and was probably just looking for a friend. What are the odds that someone like this would actually purchase a dog tag?

CDPs on the other hand, focus on collecting first-party data. This is data collected directly from a customer and helps determine how accurate your data can be. These are customers you know, have had interactions with in the past, or have even purchased from your business already. It’s tangible data with a face associated with it.

CDPs also distinguish themselves from DMPs by another factor: persistent customer profiles.

DMPs aggregate information from various data points, just like CDPs. They use this data to organize segments and build audiences for targeted ad campaigns. This is again, similar to what CDPs can do. These audience segments however, are not persistent profiles. Since DMPs are cookie-based, the data collected lasts for as long as a cookie does – 90 days.

CDPs contain data that don’t have an expiration date. This data can continue to grow, to enrich a customer profile over its lifetime, and keep it evergreen. This is what it means to have a persistent customer profile.

CDPs are great for overall marketing activities that aren’t just limited to advertising. It has data integrations that spread its reach across the entire customer journey, not just limited to customer awareness and onboarding.

cdp-vs-dmp

Again, CDPs are not touted to be substitutes of a DMP. DMPs were intended for advertising purposes and it would make no sense for a DMP to keep data that’s more than several weeks old. Think about it, someone who is looking for a washing machine, will not be looking at buying a washing machine forever now, will they?

Ultimately, CDPs can be distinguished from DMPs by a single statement: DMPs are for advertisers; CDPs are for marketers.

Overview of CDP, CRM and DMP

CDP CRM DMP

Collects data on existing as well as anonymous individuals

Can only store data on existing leads or customers

Collects data on anonymous individuals

Analyzes customer behaviour to make predictions about a customer’s future activity

Primarily used to make sales projections and view the sales cycle

Captures audience data for campaign targeting purposes

Ingests identity data, behavioral data, online & offline data, to create comprehensive profiles

Contains basic identity data and cannot collect offline data unless entered manually

Stores probabilistic data that builds anonymous profiles

Collects first-party and second-party data regularly which never expires to create an evergreen profile

Collects first-party data only

Typically collects third-party data that usually expires after 90 days

Collects anonymous data and later adds personal identifiers (PII)  to unknown individuals

Collects known data only

Collects anonymous data but individuals are linked by non-PII like cookies or IP address

Designed to support all kinds of marketing activities

Designed to support sales functions

Primarily designed to support adtech and advertising

What kind of data does a CDP need?

CDPs are versatile pieces of technology that love data. 

Today, data comes in many forms and from many places. With the world increasingly becoming cross-channel and mobile app-centric, it isn’t surprising that CDPs need to be well-equipped to handle any kind of data that is available across mediums. 

Primarily, this data is customer data.

There are different types of data that fall under the broad term of customer data. Here are a few types of data that constitute customer data as a whole:

Contact information and identity data

The first thing we look at when we talk about customer data – their identity. Identity is at the core of every individual, and understanding who you are interacting with is the first step to personalization.

Identity data can also be referred to as Personally Identifiable Information (PII). This is important, as this information helps CDPs create associated identifiers for each customer.

Identity data comprises of the following:

  • Name (first, middle and last)
  • Current physical address
  • Email address
  • Date of birth
  • Contact information (mobile phone number, landline number)
  • Login details
  • Government issued ID (Driver’s license number, SSN, passport number,)
  • Social security number
  • Bank details (Bank account number, credit/debit card number)

Qualitative data 

Qualitative data raises the blinds and lets you understand the customer. It helps marketers gain some perspective and interpret what a customer could be looking for. This type of data is vast and can give a lot of insight into customer behavior, attitude, and customer engagement. 

Qualitative data can broadly be classified into engagement, behavioral, and emotional data. Let’s take a closer look at all three.

Engagement data

Engagement data gives you quantifiable data. From email click rates to the number of times a customer visits your website, engagement data tells you how interested your audience is. It is tangible data that can help marketing teams discern how well a campaign performed, or how successful a product launch was.

Engagement data includes the following:

  • Social media engagement rates
  • Video view count
  • Campaign conversion rates
  • Website traffic
  • Email open rates and click-through rates
  • Customer queries and demo requests
  • Invite acceptance rates
  • Ad clicks and conversions
  • Gated content downloads

Behavioral data

Behavioral data can reveal a lot about a customer’s decision-making and help observe patterns within a customer journey. To feel and sound relatable to your customers, understanding what makes them tick is a great way to establish a deeper connect and relevancy amongst your audience.

While there is a lot of overlap between behavioral data and engagement data, behavioral data gives more insight into how frequently a customer is engaging with a business.

Behavioral data can provide insights such as:

  • Duration for which a customer stays on a webpage
  • How frequently a customer orders a product
  • What hours of the day is the customer more prone to visit a website
  • Average customer spend 
  • Which days of the week is the customer least active

Emotional data

This is an important source of data to look into considering emotions are what makes us humans at the end of the day.

Emotional data refers to information on a customer’s feelings, attitude toward a product, and likeability. Since this isn’t tangible data, it can become tough getting concrete insight that can be fed into a software. 

To get around this issue, emotional data needs to be presented in conjunction with something quantifiable, in order to make it more tangible. One way of doing this is by using surveys and evaluating customer satisfaction. Since most of these surveys are evaluated on a numeric scale, it becomes easier to associate a number to a feeling.

Emotional data collects the following information:

  • Customer satisfaction
  • Opinions on a certain product or service
  • Customer sentiments
  • Attitude toward physical traits
  • Customer pain points
  • Likes and dislikes toward a certain product or messaging

Benefits of a CDP

Contrary to what it may seem, CDPs aren’t just data warehouses. They do ingest a ton of data, but they serve a multitude of purposes. Here are just a few of many benefits that a CDP exhibits.

Enhance customer experience

The whole philosophy of a customer data platform is to use data to understand customers better. Better understanding = better relationships.

Customers today are bombarded with ads, campaigns, messaging on every device they look at. It’s gotten to the point where most customers have become hyper-aware of the ads they’re being presented with. Banner blindness has become a real thing where consumers block out elaborate display ads.

Today, campaigns are controlled by the consumers. YouTube’s “Skip Ad” button allows viewers to click away from an advertisement. Google carefully chooses which ads to push on the average internet user. Consumers can very easily click on the button that would “Stop showing this ad.”.

Consumers are contributing to the already growing segmentation process by choosing what they’re willing to tolerate – and what they will pull the ad blocker on.

This is why personalization becomes key in all marketing activities.

In the yesteryears, a nationwide campaign blaring on every television set in between shows was the only way brands could connect with the audience. Today the opportunities to connect with consumers may have increased via online and offline channels, but a business’ ability to reach them in a meaningful way has become tremendously challenging.

With CDPs, the data that gets accrued can be used to create relevant messaging. Consumers won’t feel averse toward campaign efforts if what they’re being presented is personally relevant. This enhances the overall customer experience with a brand and increases customer retention.

Reach niche audience segments

CDPs make granular segmentation work like a dream. Marketers have a finite amount of budget at their disposal. Every dollar counts when it goes into paid campaigns. Targeted ads aren’t a novel idea. This approach has been used by countless marketers and ad managers. 

Look at LinkedIn ads.

When setting up a campaign for a period of time, LinkedIn offers a ton of filters to narrow the audience down to a specific set of people. Most of these filters are demographic, geographic, designation, industry, company name, etc. 

But what if you wanted to target all the Chief Technology Officers of neobanks in Kenya who are looking for a loan management software, and had stumbled onto your website, but never requested a demo?

That’s how granular a CDP can get. To be fair, campaign platforms like LinkedIn get pretty close to filtering the audience that you are looking for. Over the course of 2020, the worldwide ad spend increased by 56.4%

More businesses have accelerated their online campaign efforts. What you might be paying for a campaign for a general audience could be half of what other businesses are willing to shell out. And we all know the golden rule: the highest bidder always wins.

Targeting extremely niche segments that are certain to buy or interact with your product, is the best way to spend that marketing budget.

Organizing all the data

Data is amazing. It’s what makes the world function, makes tasks more accurate, and answers a lot of questions. There isn’t such a thing as too much data, but there definitely is such a thing as too much unorganized data.

The most obvious benefit that can be seen immediately with a CDP is data organization. Most marketers already play around with a few martech tools at their disposal. All these tools are proficient at what they do, and accumulate a ton of data.

It’s what happens after the data has been collected that poses a bit of a problem. 

As your business grows, so does your target audience. This results in multiple “moments” of interactions. Your web analytics tool will tell you how many hits your website had. Your automation tools will tell you how many form sign-ups your landing pages received. Your email tool will tell you how many people opened the last email campaign that was sent out.

All this is great information to have at hand, but what if you wanted to study the journey of one individual?

CDPs take all this data and clean it up for a much easier overview. By integrating with every tool you have at our disposal, a CDP can create one consolidated data central, and segregate common data under a persona. 

Duplicated data is removed, and all the data on a CDP is synced with real-time data inflow. CDPs break data silos and create one unified platform for all the data under the sun. Think of it as a Wikipedia for all your customers.

Improved data protection

Data privacy has gotten quite sticky over the past decade. With laws and regulations set in place to protect users’ data, it becomes imperative to keep data privacy at the forefront of any strategy.

The General Data Protection Regulation (GDPR) legislation requires businesses in the EU to comply with data governance practices. Incompliance with these practices can affect businesses dearly. There have been many cases where customer data that was taken without consent, has resulted in legal battles with corporations. 

Case in point: Target

Target took consumer data, for promotional activity. While they got promotion, it wasn’t the kind the retail chain was looking for.

The campaign was for their maternity section, where they sent out coupons for all maternity-related items, to women who they believed were pregnant based on customer data they got their hands on. One such recipient of this coupon was a teenage girl, which revealed to her family about her pregnancy in the worst way imaginable.

Since CDPs primarily collect first-party data, businesses know that the data they have is accurate, and more importantly, obtained through consent. Creating a well-thought-out data governance practice and using a CDP alongside is a surefire way of making sure the data on your hands is just what you need without ruffling too many feathers or facing legal implications.

CDPs are a marketer’s best friend

According to the CDP Institute, "A CDP puts marketing in direct control of the data unification project, helping to ensure it is focused directly on marketing requirements."

One huge benefit of having a CDP is the fact that it’s designed keeping marketers in mind. Marketing should be smart and data-driven, and a CDP is the platform to get there.

Not only does a CDP act like a Wikipedia page, that constantly updates its data to stay relevant, it can be a powerful customer analytical tool as well. 

Since the data is organized neatly into personas and profiles, it becomes easy to generate reports and build attribution models. Assessing which activities have shown favorable results and by what numbers exactly, can help marketers create tangible models and graphs that consistently reveal campaign progress and marketing growth.

Not having to compute data from discrete systems helps marketers work smarter, not harder.

Top 5 customer data platforms

The list below contains real-user reviews for the best customer data platforms on the market. To qualify for inclusion in the customer data platform (CDP) category, a product must:

  • Clean and deduplicate data across disparate systems to provide a unified and comprehensive customer profile
  • Enhance marketing campaign targeting performance by providing relevant audience lists
  • Offer a 360-degree view of every customer
  • Facilitate cross-channel and multi-channel communication to allow seamless campaign launches
  • Collect and unify first-, second-, and third-party data from a variety of online and offline channels and mediums, and store it onto a single platform

* Below are the five leading customer data platforms from G2's Spring 2021 Grid® Report. Some reviews may be edited for clarity.

1. Segment

Segment is a customer data platform that enables marketing teams with a single view of customers and offers them personalized experiences throughout their journey. It offers propensity modeling that helps marketers predict the prospect of a customer making a purchase.

What users like:

“By implementing one API, we can be free to use as many downstream tools as we wish. What's more, by standardizing on a single event API our team is forced to think critically about what events are important to be tracked, and an event in one platform means the same thing as an event in another platform. Segment also makes it easy to take the same event stream and archive it off to a data warehouse, such as Redshift or Snowflake, and create a single source of truth."

 Segment Review, Jordan H.

What users dislike:

“Some things that should sometimes be simple are not possible and require custom development on our side. For instance, it is not possible to filter logs from a source to a destination by looking into a user's traits (either custom or computed), even though the userId is available in the log and a simple lookup table should theoretically do the trick. We end up having to write a lot of custom functions and loopbacks, and it gets a bit messy.”

 Segment Review, Julien W.

2. Emarsys

Emarsys is an omnichannel marketing automation tool featured as a part of the SAP Customer Experience portfolio. The solution is integrated with their Customer Experience Platform and offers multi-channel campaign management, audience segmentation, and dashboards to track customer lifecycles.

What users like:

“Emarsys is the best marketing solution available in the marketplace. Emarsys is user friendly. Easy to use and very helpful in marketing business. The dashboard is easy that any user can create campaigns and make it live easily for the business. The integration of emarsys with other software’s are also on point. The user can use it with no hindrance. Quick, fast, and responsive to the actions.

The support team is the biggest edge of working on Emarsys, they are always available from start to end. They helped from installation to creating different campaigns and providing solutions to users for a better program experience. Emarsys is pretty easy to use as the training session makes it easier to work on. Emarsys offers customized communication to the customers which is the biggest pro of emarsys that makes it stand out in the market.”

 Emarsys Review, Himid-Lução O.

What users dislike:

“Tracking in-store performance has been a challenge which has made things difficult to track omni-channel performance. This issue was mainly on our end, however, Emarsys was able to come up with new features that were able to resolve this and take our marketing efforts to the next level.”

 Emarsys Review, Vicken B.

3. Exponea

Exponea is an end-to-end customer data platform that collects customer intelligence from a host of data sources to analyze customer behavior, and enable marketing teams to launch omnichannel campaigns and push personalized messages to the target audience.

What users like:

“Exponea helps us to fill our inside data with website data, and we can work with them afterward! The best tool ever. Exponea helps us to fill our inside data with website data, and we can work with them afterward! It is a great tool for multi-platform communication, including email delivering oversight features, and they are stunning! I love how easy you can plan email campaigns for specific customers, customer segments. 

You can trigger by time, event category, etc. . It is also very helpful to see how many customers really open emails and how many of them click on links in the email. It gives me great feedback and helps me to understand how to attract them and what their motivation is. I use scenarios a lot, and I can tell you that it is spectacular how timesaving is this awesome tool.”

 Exponea Review, Martin N.

What users dislike:

“Exponea is a tool that has a lot of great features but if I had to think of something I dislike, it would be the email tool that is not as intuitive as all other ESPs out there. There is also the fact that it is geared toward the retail industry and has not got all the tools needed for publishers such as integration with Google Ad Manager to serve ads to audiences instead of contextually.”

 Exponea Review, Brice A.

4. Insider

Insider is a multichannel growth management platform that creates customer segments through data unification. It matches profiles through data from surveys and cross-channel sources and creates AI-backed segments that are the result of predictive modeling tools.

What users like:

“The ability of Insider’s products to adapt quickly and innovate based on the digital trends is something we love about the platform. The professional support from their account management team, the ease of use and more importantly the advanced personalization scenarios that are made possible has helped us design some highly performing campaigns that are individualized to each users preferences. 

One of their products, InStory is something that has helped us drive some really spectacular results. We’ve been able to deliver social-media-like experiences on the desktop and mobile web and coupled with their advanced segmentation features, we were able to target niche audiences with high performing personalized content.”

 Insider Review, Yasemin Y

What users dislike:

“We would like to see Insider’s panel become available for the mobile platform as well. Since we update our web push content in real-time, it would be easy to be able to do it from a smartphone as well.”

 Insider Review, Natthanun K.

5. Optimove

Optimove is a relationship marketing hub that ingests data to provide a unified view of a customer and enables marketers to act on this data to push multi-channel messaging. Optimove has an AI bot, Optibot, that provides actionable recommendations and customer insights.

What users like:

“Optimove is a great segmentation tool, which we use to plan, execute, measure, and optimize our marketing activities. It uses a very clever algorithm of segmenting customers based on their behavior, which allows us to send the right offer to the right group of customers, increasing the pick-up rate.

Optimove provides easy to read and transparent analytics, which allow us to check the performance of each campaign separately as well as compare target groups and analyse customers' migration.

Our account managers are always helpful, they systematically provide team training and assist us in resolving issues.”

 Optimove Review, Alena V.

What users dislike:

The Journey creator can be improved with the introduction of a lifelong control group, to allow the cross comparison between different journeys. Also, insights gained through Optibot's recommendations can be further improved to become more tailored to Gaming or Retail, depending in which industry the operator belongs to.

 Optimove Review, Athina Z

 

Customer data platforms are the maps marketers didn’t know they needed

Data can sometimes seem infinite. Cutting through all that noise just to find what exactly you’re looking for can be a Herculean task, especially if you have all your data spread across disparate systems. CDPs act like a map when it comes to assembling all that data and pointing out which way to go.

Want to keep your customers happy? Check out our guide on database marketing to see how you can market to your audience smarter.

customer-data-platforms
Take good data and make it great

Get a 360-degree view of your buyer and drive engagement with a customer data platform.

customer-data-platforms
Take good data and make it great

Get a 360-degree view of your buyer and drive engagement with a customer data platform.

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