Beyond the Single Customer View: Capturing Omnichannel Customer Journeys

The single customer view, the “golden record” of customer data, is an idea that businesses have been pursuing for a long time. Having one view of customer data is essential for personalization and customer experience.

Usually, a single customer view provides an aggregate, historical view of customer data that encompasses every touchpoint your customers have with your business. It can show you channel performance, and average CLV or churn rates. And it can help surface influential touchpoints along the customer journey. Marketers can use this information to develop personalization strategies based on past performance.


of retailers reported personalization drove a 50-100% increase in revenue.


But recently, marketers are chasing something more sophisticated. We are now trying to deliver one-to-one personalization, and seamless experiences across channels. And we are trying to do it in the moment when the customer is engaged, rather than the day after.

That means marketers need something beyond the aggregate, historical view. Something that can help them move at the speed of the customer. What’s needed is a unified view of each individual customer’s omnichannel journey.

However, gathering all the necessary data in one place can be difficult. For the aggregate view, you could simply import data from each of your marketing platforms and stitch it together. But this doesn’t allow for the level of granularity you need for individual customer journeys.

If you can put the data together, an omnichannel view of individual customer journeys is the fabric for exceptional improvements in customer experience and business efficiency.

To achieve this, you need the following capabilities:

  • First-party tracking

  • Identity resolution under a first-party ID

  • Data from all customer data systems integrated in one place

  • A constant stream of customer activity, updating in real time

  • Machine learning

Let’s discuss why these things are important.

1. First party tracking

First-party tracking uses cookies, and tags that have the same web domain as the business using the tag ( cookie running on First-party trackers can be planted on a website, and on other digital properties used by the brand. They aren’t yet widely used by brands, just because of the way online advertising has operated until now. Most online data collection happens through third-party cookies.

A third-party cookie has a different domain address than the website it’s running on ( cookie running on In response to privacy regulations, major internet browsers are restricting third-party cookies. In some cases third-party cookies are erased after a single day, and in some cases they are blocked altogether. This makes it impossible for a brand to get an accurate stream of behavior data, because one customer ends up looking like many.

First-party cookies are not being restricted by browsers. And they are less affected by ad blockers, because they won’t be flagged as a ‘foreign script’ running on the page. So using first-party tracking assures the quality of your customer journey data. And as a result, you are better equipped to deliver the seamless cross channel personalization your customers want.


of customers say the experience a company provides is as important as its products and services.


2. Identity resolution under a first-party ID

Identity resolution is how you make sure you are capturing the full journey of one customer, rather than multiple fragmented pieces.

A first-party ID is an inherent result of using first-party trackers. Within the Velocidi CDP, the first-party identifier acts as the “master ID” to which IDs from all other systems are matched.

Having an identifier associated with your first-party tags is a powerful advantage because your first-party tags are already used in multiple channels (your website, your emails, social and display campaigns). As a result, your CDP recognizes customer interactions across channels even before importing external IDs. With the addition of external IDs, it becomes much easier to gain a high quality deterministic ID graph.

When the separate user IDs, (device IDs, logins, browser IDs) are resolved into one profile, any customer interaction associated with any of those IDs is recorded in one continuous customer journey stream.

Back up. Deterministic what now?

A deterministic ID graph is a method of identity resolution that uses only the factors that are absolutely certain to indicate an ID match. The other common method is probabilistic matching, which uses more loose connections to create ID matches that are likely but not 100% certain.

The value of deterministic matching was downplayed in the past because it was heavily reliant on third party IDs and PII (personally identifiable information) such as Facebook logins, or loyalty IDs. It had a scale issue that made it impractical for some types of marketing campaigns. That was because people didn’t have the first-party tracking capability we have today. Now you have a first-party ID that identifies both known and unknown users without PII. So it’s safe, compliant, accurate, and scalable.

3. Data from all sources integrated in one place.

A single customer view is as much a result of connecting your existing data sources as it is about adding anything new. Connecting the “data pipes” between all your different data sources is essential no matter what. However, in order to get the omnichannel customer journeys we are aiming for, your first-party data is still the main fabric.  

As we just touched on in the previous section, much of what makes up the digital customer journey can be captured in your first-party data. This is especially true for DTC brands, who are managing their marketing in house as much as possible. Velocidi enables you to place first-party tags on your website, emails, and ad campaigns. And the platform can import and integrate customer data from your CRM, POS, or customer service systems.

4. A real-time stream of data

An aggregate-level single customer view is not expected to be updated more than once a day. It can be less frequent, depending on how it’s being used. But, if you’re going to make good use of individual customer journey data, it needs to update in as close to real-time as possible.

Individual customer journeys are never in stasis. Therefore your customer journey data must reflect real-time activity in order for it to be actionable at a speed that is relevant to the customer.

5. Machine Learning

OK! Now that we’ve covered the more mechanical aspects of customer journey data, let’s dive into the one thing that makes all of this worth something: machine learning.

Marketers are a knowledge-hungry bunch. You want to know everything about what works and why and what they can do to make it better. That’s what makes you great at your job. BUT, this is not humanly possible in the case of individual customer journey data.

Customer journeys are unique to the individual. Different channels, different pacing between journey stages, different ad frequency tolerance. A machine learning algorithm can be trained to take all of this into account and make predictions at a speed that is actionable in real-time campaigns.

In the Velocidi CDP, machine learning models make customer journey data actionable by automatically generating customer attributes for segmentation. Attributes are generated as soon as a new customer profile is created. So predictions for customer lifetime value (CLV) or likelihood to purchase are available immediately, based on the current data. These predictions continue to change and improve with every new interaction that is recorded in a customer profile. Over time it becomes more and more accurate.


of customers expect companies to anticipate their needs.


So, you as the human marketer probably won’t get much use out of manually poring through customer profiles. They are there in your user interface mainly so you can make sure the CDP is working properly. But you get much more value from the individual customer journeys by making using of the machine learning output to create intelligent audience segments for campaigns. And once you have the segments, it’s up to you to come up with a tailored creative messaging strategy to guide customers through journey stages.


Speaking of…

So far pretty much everything we’ve talked about in this article actually takes place with little to no effort on your part. It’s built into the CDP, and we help you get everything connected and set up during your onboarding process. So now that you have your real-time stream of individual customer journeys, here are some examples of what you can do with it.

Speak to each customer with a consistent message across all channels, and tailor the message to their journey stage.

Omnichannel ID matching, omnichannel customer journeys, of course we’re going to also help you with omnichannel campaign delivery. If you run multi-channel campaigns, activating audiences through your CDP can help you keep message delivery relevant to each customer in response to real-time interactions.

Make ad spend more efficient by keeping ad delivery focused on only the most receptive audience.

Read our Barkyn case study. They doubled their ROI by doing this.


increase in retention can result in up to


increase in profitability.

Bain and Company

Here is what happens when you do these things:

  • More efficient budget allocation

  • Higher return on ad spend (ROAS)

  • Better retention rates

  • Lower customer acquisition costs (CAC)

  • Better customer experience

  • Faster business growth.

Thanks for reading! Make sure to get in contact with us if you have questions or would like to chat about we can help you capture individual customer journeys.

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