“We are all experiencing a massive explosion of data,” said Leslie Lorenz, head of North American retail industry at Snowflake, in her presentation at The MarTech Conference. It’s no surprise, then, that her brand is also “getting many [brand] requests that say they want to be data-driven.”
Most marketers would agree access to more customer data is a good thing for brands. Yet fragmentation, duplication, and other issues can often disrupt campaigns. Brands need ways to concentrate customer data and create a unified source of truth.
“How we bring all of that data into one place is the challenge,” she said. “What we’re ultimately seeking is the ability to bring data together to discern each customer interaction and its contribution to revenue. It’s going beyond basic business rules like first-touch and last-touch and moving toward data science models that incorporate the nuances of each customer touchpoint.”
Lorenz says the key to addressing these issues is creating a fully data-driven marketing tech stack. Here are some steps to begin the process.
Identify the causes of fragmented data
There are a slew of technologies available to marketers that collect and analyze customer data. However, these same assets can end up working against them. How? Data siloing.
“Each one of these different applications that we’re using, and all of the different customer touchpoints, are just creating more data silos,” said Lorenz.
Addressing data siloes is no simple feat — marketers need to investigate the root causes of the issue, being careful not to disrupt their current data collection processes. Fortunately, data integration tools can help identify these problems by centralizing information from each customer touchpoint.
Once the data issues are identified, marketers will have a better grasp of their customers and potentially pinpoint the causes leading to poor experiences.
“What is needed is a seamless way to understand everything customers are doing,” said Lorenz. “[Understanding] their needs and how they want to be engaged, ultimately tying that back into the internal organizational data set or sales.”
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“Most of this starts with data capture,” Lorenz said. “How do we get our data into the single source of truth? This involves different types of data, whether it be advertising data, first-party data, or more traditional marketing data implementations.”
An effective marketing tech stack unifies platforms and services to share data and create a cohesive story of the customer experience. Using data unification tools can help ensure these stacks avoid generating data silos.
Lorenz highlighted some of the effective ways her brand is building its data stack: “We pull data via ELT [extract, load, transform] tools, streaming tools, or data sharing capabilities into our tech stack. And once it’s in our data tech stack, we set up the ability to process that data.”
Prioritize digital transformation tasks
Digital transformation is the process in which brands transition their operations to digital systems to better understand customers. The tasks involved encompass a wide range of activities, including personalization optimization, omnichannel engagement and marketing attribution enablement.
“Our first step was just enhancing what we currently had — the current view of the customer,” she said. “We used that to get an understanding of how to make our engagements more relevant to our customers and how to drive toward personalization.”
In addition to increasing personalization, Lorenz recommended that marketers focus on transforming omnichannel experiences and marketing attribution systems.
Omnichannel engagement.Omnichannel tactics go beyond multichannel approaches (something they’re often confused with) to help marketers gain that full view of the customer. By centralizing customer data via a CDP or other data tool, marketers can better understand their audience’s preferred touchpoints, using that knowledge to enhance experiences across all channels.
Data-driven marketing attribution. Improving customer experiences relies heavily on optimizing marketing attribution. If you don’t know which touchpoints or behaviors are contributing most to the bottom line, it’ll be difficult to create a sustainable marketing pipeline. Employing marketing attribution tools is a great way to identify these activities.
Lorenz believes these transformative tasks, centered on data, can help marketers create tech stacks that enhance customer experiences.
“We used the data to create a better connection with our customers,” she said. “[We created] a better brand experience and found a better use for our marketing dollars, which helped us understand how we can best move forward and grow the organization.”
Snapshot: Data management platforms
For years marketers and advertisers have used data management platforms, or DMPs, to manage audience information. This software houses preference, behavioral, and demographic data in a centralized location so marketers can craft targeting segments for their campaigns.
DMPs collect data from consumers on many platforms. Yet the amount of information marketers and brands use is limited. The advent of privacy regulations such as GDPR and CCPA has encouraged companies to increase data collection transparency, building more trust among customers.
In addition to their storage and organizational capabilities, DMPs make campaigns easier by communicating with customer data platforms (CDPs), demand-side platforms (DSPs), and other marketing technologies. The DMP pulls in first-party data from these platforms, analyzes it and identifies key growth opportunities, then funnels it back to the original source. These capabilities have led to big players such as Adobe and Oracle adopting the technology.
Marketers can use DMPs to transform their campaigns. By collecting data from many campaigns, you can create even richer datasets than if they were analyzed individually. Building audiences and organizing customer data has never been easier. Learn more here.
About The Author
Corey Patterson is an Editor for MarTech and Search Engine Land. With a background in SEO, content marketing, and journalism, he covers SEO and PPC to help marketers improve their campaigns.
The author’s views are entirely his or her own (excluding the unlikely event of hypnosis) and may not always reflect the views of Moz.
Nike.com uses infinite scrolling to load more products on its category pages. And because of that, Nike risks its loaded content not getting indexed.
For the sake of testing, I entered one of their category pages and scrolled down to choose a product triggered by scrolling. Then, I used the “site:” command to check if the URL is indexed in Google. And as you can see on a screenshot below, this URL is impossible to find on Google:
Of course, Google can still reach your products through sitemaps. However, finding your content in any other way than through links makes it harder for Googlebot to understand your site structure and dependencies between the pages.
To make it even more apparent to you, think about all the products that are visible only when you scroll for them on Nike.com. If there’s no link for bots to follow, they will see only 24 products on a given category page. Of course, for the sake of users, Nike can’t serve all of its products on one viewport. But still, there are better ways of optimizing infinite scrolling to be both comfortable for users and accessible for bots.
Unlike Nike, Douglas.de uses a more SEO-friendly way of serving its content on category pages.
They provide bots with page navigation based on <a href> links to enable crawling and indexing of the next paginated pages. As you can see in the source code below, there’s a link to the second page of pagination included:
Moreover, the paginated navigation may be even more user-friendly than infinite scrolling. The numbered list of category pages may be easier to follow and navigate, especially on large e-commerce websites. Just think how long the viewport would be on Douglas.de if they used infinite scrolling on the page below:
Let’s check if that’s the case here. Again, I used the “site:” command and typed the title of one of Otto.de’s product carousels:
As you can see, Google couldn’t find that product carousel in its index. And the fact that Google can’t see that element means that accessing additional products will be more complex. Also, if you prevent crawlers from reaching your product carousels, you’ll make it more difficult for them to understand the relationship between your pages.
To find out, check what the HTML version of the page looks like for bots by analyzing the cache version.
When scrolling, you’ll see that the links to related products can also be found in its cache. If you see them here, it means bots don’t struggle to find them, either.
However, keep in mind that the links to the exact products you can see in the cache may differ from the ones on the live version of the page. It’s normal for the products in the carousels to rotate, so you don’t need to worry about discrepancies in specific links.
But what exactly does Target.com do differently? They take advantage of dynamic rendering. They serve the initial HTML, and the links to products in the carousels as the static HTML bots can process.
However, you must remember that dynamic rendering adds an extra layer of complexity that may quickly get out of hand with a large website. I recently wrote an article about dynamic rendering that’s a must-read if you are considering this solution.
Also, the fact that crawlers can access the product carousels doesn’t guarantee these products will get indexed. However, it will significantly help them flow through the site structure and understand the dependencies between your pages.
It’s impossible to fully evaluate a website without a proper site crawl. But looking at its robots.txt file can already allow you to identify any critical content that’s blocked.
This disallow directive misuse may result in rendering problems on your entire website.
To check if it applies in this case, I used Google’s Mobile-Friendly Test. This tool can help you navigate rendering issues by giving you insight into the rendered source code and the screenshot of a rendered page on mobile.
But let’s find out if those rendering problems affected the website’s indexing. I used the “site:” command to check if the main content (product description) of the analyzed page is indexed on Google. As you can see, no results were found:
The layout is essential for Google to understand the context of your page. If you’d like to know more about this crossroads of web technology and layout, I highly recommend looking into a new field of technical SEO called rendering SEO.
Lidl.de proves that a well-organized robots.txt file can help you control your website’s crawling. The crucial thing is to use the disallow directive consciously.
Having a large e-commerce website, you may easily lose track of all the added directives. Always include as many path fragments of a URL you want to block from crawling as possible. It will help you avoid blocking some crucial pages by mistake.
Will users get obsessed with finding that particular product via Walmart.com? They may, but they can also head to any other store selling this item instead.
To fix this problem, Walmart has two solutions:
Implementing dynamic rendering (prerendering) which is, in most cases, the easiest from an implementation standpoint.
IKEA proves that you can present your main content in a way that is accessible for bots and interactive for users.
When browsing IKEA.com’s product pages, their product descriptions are served behind clickable panels. When you click on them, they dynamically appear on the right-hand side of the viewport.
Take care of your indexing pipeline and check if: