The digital evolution of the last 15 years has been staggering.

Consider 2005. We had no iPhones or tablets. Facebook was seven years away from its record-breaking IPO, with an active userbase of less than 1% of what it is today. The market caps of the other big three horsemen of tech (Apple, Amazon, and Google) were a small fraction of what they are today. And the number of connected devices per person was one — barely.

As we head into 2020, the number of connected devices to grow to just over 6.5 per person. Smartphones, tablets, wearables, smart speakers, and miscellaneous IoT devices give us more ways to connect than ever. And the hyper-growth of social media has created more touchpoints along the way.

This has radically changed how we interact across the board. And it has transformed shopping journeys.

When it comes to commerce, customer journeys are now more fragmented than ever. With more ways to connect, be influenced by, and marketed to, shoppers traverse the awareness, consideration, and conversion phases more frequently and more quickly. Marketers need to not only understand these broken journeys but also be empowered to intervene in them.

Attribution modeling and its challenges

One way marketers try to gain insight is by using attribution modeling — a technique that determines how to credit the contribution of specific actions to a conversion. As marketers well know, this isn’t easy.

Attribution modeling starts with the final conversion, then applies a model across the touchpoints. I understand why many marketers use it. It at least allows them to look beyond the last click leading to a conversion.

But attribution modeling has its challenges. First, customers can purchase offline. Second, external influences could be a strong driver for the conversion. In any event, attribution modeling is not a true measure, but rather a calculated guess of the causal influence of each touchpoint on a conversion.

The reality is you need to measure each individual interaction at a micro-level and define the value of each as it pertains to visitors’ propensity to convert.

You need engagement data — across the journey

Consider a bird’s eye view of a shopper’s experience at the Acme Store.

After entering, the shopper proceeds to an aisle, stops midway to look at a product, views similar products, returns to the one they initially looked at, picks it up, reads the back of the box, and looks over the other color and size options. It’s only then that a perceptive salesperson, observing a growing propensity to purchase, steps in to ask if they have questions. After a brief discussion, they purchase the product.

Note two things here. First, the salesperson let the customer guide their journey, observed what we might call their “micro-engagements,” and intuited the appropriate time to step in.

Second, from a last-step attribution perspective, it was the conversation with the salesperson that led to the purchase. And if the conversation was the cause, then the salesperson should have gone in quicker. There’s no reason to wait around, after all, when waiting will only offer a chance for the customer to waver.

But the reality is this: if the salesperson had gone over sooner, the customer would have felt crowded and left. The salesperson understood this, watched, and waited for the right moment.

Equivalent engagements happen online constantly.

On a typical product detail page, for example, a buyer will scan multiple images of a product while scrolling the depth of the page, view additional product content such as specifications and reviews, check available variants such as size or color, watch product videos, and possibly chat with a bot or online sales representative.

Digital marketers need to understand their customers’ journeys in a similar way to how the Acme salesperson did. But while digital marketers can’t watch and intuit the movements, mannerisms, and overall mood of their customers while they shop, they can gain access to actionable insight.

Sitecore developed the Engagement Value score as a way to empower marketers to do online what a competent salesperson would do in-store. By tracking visitors’ behavior, rating each micro-engagement, and aggregating the total, Sitecore’s Engagement Value score provides a clear view of where each visitor is in their journey.

And engagement data doesn’t need to be limited to visitors’ actions. Sitecore® Experience Database™ (xDB) is an incredibly powerful tool — able to capture, aggregate, and analyze data from myriad sources. By connecting data from campaigns, web visits, and more, xDB offers exceptional insight.

In reality the checkout is not much more than administrative paperwork. We must remember that the true sale occurs when the buyer’s pre-purchase engagement with a product reaches its pinnacle.

The Engagement Value Scale above is very much weighted toward the final steps once a visitor has decided to purchase. One way to expand this is by adding product engagement goals (i.e. micro-conversions).

Why product engagement data matters and how to get it


Product engagement data measures exactly what it says — when and how products are engaged with online. All of this can be tracked quite easily. In addition to being easy to track, product engagement data enables a lot:

  • Measure marketing campaigns — are they generating product interest over hits?
  • Match products to personas — discover what personas are engaging with what products; then use this data to better target personas with products likely to appeal to them
  • Increase product and merchandising teams’ understanding — discover what products are popular vs. just highly trafficked
  • Drive product-specific personalization — when a shopper visits multiple products in the same category, which were they most engaged with?
  • Empower machine learning — data is the fuel for machine learning algorithms (the more data, the deeper the insight), and collecting product engagement data is a great way to turbocharge your machine learning engine

Additionally, should your organization not transact online, or the majority of sales occur via other channels, product engagement data has the ability to not only measure performance in your digital marketing efforts but also provide powerful intelligence about your products to the business as a whole.

With the robust marketing capabilities of Sitecore Experience Commerce, an industry standard tag manager such as Google Tag Manager, and a small extension, marketers can unlock the power of product engagement data quickly and easily, without data intervention. At Sitecore Symposium 2019 in Orlando, Rob Earlam and I showcased how to do this. Many discussions followed the presentation, with retailers and manufacturers recognizing this as a key pain point and opportunity.

In an upcoming post, I will outline how to set up your Sitecore Experience Commerce environment to capture product micro-engagement data. I will also outline how to define and develop custom aggregations in Sitecore xDB to surface collected data in a meaningful way.

With a passion for growth, improving CX, increasing lifetime customer value, and reducing cost per acquisition through digital, Jay Sanderson is the Global Experience Commerce Product Specialist at Sitecore. Follow him on LinkedIn.