Paid Media Management: How to Leverage First-Party Data for Profitable Results

Ruthie Careyby Ruthie Carey

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For marketers, data is the most valuable resource imaginable.

Thankfully, there are a myriad of ways that retailers can harvest and use data from both internal and external sources.

As far as using data for eCommerce search and shopping is concerned, first- and third-party data are going to be the most common sources.

That said, as a result of changes brought about by the GDPR (General Data Protection Regulation), as well as United States-based regulations like the CCPA and its impact on advertisers, the future use of third-party data is questionable at best.

Essentially, what both of these regulations do is to provide a certain level of transparency and control over the data that companies collect on consumers.

Because of the dynamic that these acts impose upon businesses, many merchants’ focus is shifting away from third-party data and toward their own first-party data.

As a result of this happening, today, we will explore strategies for using data for eCommerce and shopping that enable sellers to make the most of their first-party data for prime PPC results.

With that, let’s start by building a solid foundation of knowledge by covering the different types of data retailers might collect.

What Is First-Party Data?

For the uninitiated, first-party data is defined as data that a company collects on its own audience, meaning customers, website visitors and the like.

Pretty simple, right?

While first-party data is collected by a company on its audience, this does not mean that the organization’s website is the only place where data is generated and harvested. In fact, there is a range of sources from which sellers can collect first-party data, including:

  • Websites: The brand’s website is likely to be the main source of first-party data. A company’s site can serve to provide merchants with data on visitor data like names, email addresses, browsing behaviors, preferences, transactions and the like.
  • Mobile apps: Since brands will have to develop an application for their store, it is up to that company which user events are meaningful enough to harvest data on and to measure.
  • Email and SMS: Those harvesting data from email platforms can collect information on metrics like open, click and bounce rates that (ideally) span the history of the brand’s marketing efforts. Similar data sets can be harvested from users that allow a brand to engage with them via SMS.
  • POS and CRM: Point of sale (POS) systems and customer relationship management (CRM) platforms can be a boon for using data for eCommerce search and shopping as brands can use these systems to understand a consumer’s shopping history as well as broader trends around which products are selling and which are not.
  • Call centers and customer service teams: Customer service teams can be a great source of first-party data as consumers will often contact a representative with common questions and problems that the brand might not be aware exist. At the same time, many consumers will create accounts this way, thereby providing access to their name and contact information.
  • Google Analytics: While there are many misconceptions about Google Analytics, this is often a primary source of information for retailers as it supplies tons of data on consumers and their online behaviors.

One of the greatest aspects of using first-party data for PPC advertising is that retailers already own the data, meaning that they do not need to invest in potentially questionable second- or third-party information.

However, on the flip side of that coin, one of the biggest challenges to using first-party data is that it is often spread out across a multitude of different platforms. As a result of this dynamic, the data points are rarely connected and used to develop a more comprehensive picture.

For instance, many retailers will collect behavioral data on users in a web analytics platform. At the same time, they will amass customer information in their CRM system. However, in the grand scheme of things, only a small number of companies will connect the data sources to generate more actionable insights.

Therefore, when it comes to using data for eCommerce search and shopping optimization, a critical first step is to integrate a brand’s most important data sources.

With this understanding of first-party data, let’s go ahead and take a quick look at what second- and third-party data are to avoid any potential confusion.

Second- and Third-Party Data Defined

Plainly put, second-party data is merely first-party data from a trusted partner. As HubSpot defines the term:

“Second party data is information that you didn’t collect yourself – in other words, you’re using it secondhand. It’s sometimes used between trusted partners who come to an agreement to share audience insights if it would be mutually beneficial to both businesses.”

Second-party data can be helpful in aiding a company to gain a more comprehensive picture of a segment of the market. Moreover, since second-party data isn’t openly sold or traded, it can often be more valuable than third-party data.

As for third-party data, this information is usually derived from an outside source that the company does not have a direct relationship with and is purchased from the provider. Generally speaking, this data tends to come from a multitude of online sources and is then aggregated, segmented and sold to retailers for advertising purposes.

However, it is important to note how the advertising landscape is shifting in regards to different kinds of data. While first- and third-party data have traditionally held a position in paid search strategies, the regulations mentioned at the beginning of this article are starting to push things in a new direction.

Moreover, the fact of the matter is that third-party data can sometimes be dubious in nature. For this reason, a 2017 AdAge study on data providers found that:

“More than 75 percent of survey respondents admitted they are not fully confident that the data they’re utilizing is hitting consumers who are in-market to buy. Additionally, 65 percent of respondents claimed they do not fully understand the origin of their data sources.”

Between governmental regulations and questionable data, many retailers are shifting away from third-party data and are relying more on primary sources for their ad targeting tactics.

Because of the transition currently taking place, it is critical that advertisers understand how to effectively leverage first-party data for their digital promotional pushes.

Before diving into the nitty-gritty of using data for eCommerce search and shopping optimization, let’s take a quick peek at the benefits that sellers can gain, as well as the challenges they might experience.

The Benefits of Using First-Party Data

As was mentioned earlier, first-party data is an incredibly valuable resource for online sellers. The reason for this is that this kind of information brings a whole slew of benefits to the table.

Some of the main benefits of using data for eCommerce search and shopping optimization, particularly as it relates to advertising, include:

Increased Campaign Relevance

First-party data provides sellers with the most accurate knowledge of customers and can serve to inspire new ways to shape the customer experience.

Depending on what an organization knows about its buyers and their behavioral patterns, sellers can craft brand experiences that are more tailored to fit an individual, thereby increasing the chances of conversion.

Creating Personalized Ad Copy

The usage of first-party data allows retailers to make adjustments and write better ad copy for the target audience by taking into account their preferences and previous engagements with the brand.

Prioritizing High-Value Leads

When running paid search campaigns, merchants might find that their PPC leads aren’t converting. There are many reasons as to why this might be an issue, including targeting the wrong keywords, producing the wrong messaging and the like.

First-party data allows merchants to understand their consumers more intimately and craft better eCommerce customer personas using analytical data, thereby helping sellers to reach those who are most likely to be interested in a company’s offerings and convert.

Enhanced Reach

By reaching a more refined customer segment through data-based customer personas, retailers can then use this framework to create lookalike or in-market audiences that will help to scale campaigns to a broader group of consumers.

Mapping the Customer Journey

Using data for eCommerce search and shopping optimization, sellers can map the buyer journey, uncovering the various steps that consumers make on their path to purchase, as well as in what order the steps are taken.

By connecting data from various channels, retailers can see how customers move from social media to the brand’s online store and then finally completing their purchase from a mobile app.

With this holistic view, merchants can segment and optimize different paths for disparate audiences, delivering the right marketing message at the right time and place and effectively guide users to convert.

However, while there are many benefits to be had from utilizing first-party data, there are also challenges that retailers face.

First-Party Data Challenges

As with most things in life, using data for search and shopping optimization is a bit of a double-edged sword in that it can provide immense value, but it can also bring a number of difficulties.

Some of the challenges that merchants are likely to encounter when using first-party data include:

Building a Data Strategy

When aiming at using first-party data, it is critical to combine information from different sources. This means that sellers will need to create a strategy that includes:

  • The sources from which data is being collected
  • Which data points are being harvested
  • How to map it across the customer journey

This strategy will ultimately serve to guide the entire process. Moreover, it must be customized for the sources and touchpoints that are relevant to the company.

Data Integration

The plain fact of the matter is that integrating data is easier said than done.

As was mentioned previously, first-party data tends to come from a variety of unconnected sources, usually third-party technology partners. Despite the fact that these partners have harvested the data for the brand, combining it all in a single place can be difficult.

Nonetheless, pulling this information from their siloed state and compiling it all in a single destination is critical for understanding the big picture and effectively using data for eCommerce search and shopping optimization.

Real-Time Decision Making

The unfortunate reality of using customer data is that it decays incredibly fast.

Therefore, it is essential to possess the systems necessary to quickly distribute data to internal teams and external partners who can take advantage of the intel before the window of opportunity evaporates.

Data Privacy

Working with first-party data means that retailers are dealing with sensitive information.

As was touched upon earlier, as regulations like the GDPR and CCPA have come into existence, marketers have had to alter how they collect and deal with consumer information.

These types of acts have served to provide the consumer with rights to understanding what data is being collected from them, knowing if their information is being sold or shared, the ability to opt-out of data collection, gain access to the data that is being collected, and similar measures.

Knowing this, it is essential that retailers are working to make sure that their first-party data is being handled in an ethical and legal way. Therefore, it is vital that sellers ensure that they are in line with CCPA compliance guidelines and those of similar laws.

With some of the benefits and challenges of using first-party data outlined, let’s go ahead and examine how retailers can put this information to use to produce profitable PPC results.

Using Data for eCommerce Search and Shopping Optimization

The fact is that there are a panoply of ways that retailers can use their first-party data to enhance their paid media management and campaign outcomes.

Some of the ways in which retailers can enhance their PPC efforts with first-party data include:

Integrating Data Sources with Google Analytics

Google Analytics is a fantastic tool for eCommerce retailers as it helps to track important metrics like conversions. That said, Google Analytics does not inform merchants on other critical sales aspects such as the ultimate outcome of a prospect and sales rep connecting over the phone or the value of a lead that sales teams convert.

In reality, the information needed for making more profitable PPC decisions includes data points such as:

  • Lead scoring data
  • Lead to sale conversion rates
  • Total sale value of generated leads

Fortunately, most customer relationship management platforms enable retailers to feed customer data into Google Analytics to help improve the quality of leads generated.

The easiest way to achieve this is to utilize data connector tools that enable the funneling of CRM data into Google Analytics. For instance, tools such as GA Connector are compatible with an array of popular CRM platforms like HubSpot, Zoho, Salesforce, Nimble, NetSuite CRM and a plethora of others.

Ensuring Budget Efficiency

Many are aware that the data retailers can harvest from their Google Analytics account can be quite valuable for optimizing ad campaigns.

The fact is that remarketing lists for search ads (RLSA) enable sellers to customize their Google Ads campaigns to target users that have taken a specific action on the merchant’s site. This allows for retailers to target (or exclude) specific audiences, namely those who have shown some sort of interest in the company and its offerings.

By creating a remarketing list comprised of those who appear to be qualified prospects, a retailer can utilize more aggressive bidding strategies to help drive conversions.

For instance, retailers can build remarketing lists of those who have visited the seller’s site a specific number of times but have yet to complete a purchase. These folks are clearly displaying patterns of interest and should be pursued more vigorously than those who have not showcased such signals.

Additionally, retailers can help to ensure bidding efficiencies by accessing the Path Length reports. For those who are unfamiliar, Google describes Path Length reports as:

“[Showing] you how many conversions and how much revenue were generated by users who saw or clicked on your ads a given number of times. For example, if a user viewed or clicked on your ads three times before converting, that conversion is included among conversions with three interactions…You can use Path Length reports to help you understand what kind of frequency is most valuable for driving conversions.”

Using this information, retailers can establish an audience list composed of prospects who appear to be on the verge of converting and target them with highly-relevant ads and forceful bidding tactics to drive sales.

Achieve Higher Target and Bidding Accuracy

First-party data can be used as a solid resource for producing more accurate targets when using Smart Bidding strategies.

While there are certainly pros and cons to Smart Bidding, it is also a feature that an increasing number of marketers are finding to be useful and profitable. Speaking to the time savings Smart Bidding can generate, HubSpot notes that:

“According to a study done by the Boston Consulting Group, 80 percent of digital marketers’ time is spent on manual tasks such as setting bids, while only 20 percent is spent on strategy. For many advertisers, automation, such as smart bidding, offers a way to alleviate this strain on marketing resources.”

Speaking to the uptick in conversions that Smart Bidding can produce, the piece goes on to state that:

“According to Google, advertisers that adopt the target cost-per-acquisition automated-bid strategy (for lead campaigns following Google best practices) see an average of 31 percent more conversions at a similar cost-per-conversion… Advertisers that choose Target ROAS see an average of 7 percent more conversions than manually set CPC bids at a similar cost-per-conversion… advertisers that automate using the search max-conversions strategy see an average 20 percent conversions uplift for all campaigns.”

Understanding the potential contained within this automated tool, assuming that sellers are feeding the program with the right data, sellers can significantly enhance their campaign performance. However, to achieve that aim, retailers must develop accurate targets.

This is where first-party data comes into play.

To make sure that automated bidding tactics are established using accurate targets, retailers can employ first-party data to conduct a post-campaign analysis before cultivating Smart Bidding strategies.

While handing the reins over to automation can sometimes be difficult, using first-party data to drive machine learning mechanisms can help to bring a sense of confidence that optimal outcomes will be produced.

Produce Better and Broader Campaign Targeting

First-party data tends to be rich regarding customer demographics, behavioral trends and other contextual information. Therefore, this naturally makes it an incredibly powerful tool for enhancing PPC targeting and retargeting efforts.

By using data for eCommerce search and shopping optimization, merchants are much more likely to produce effective campaigns that reach middle- or bottom-of-the-funnel users.

However, it isn’t just better targeting that first-party data allows. The fact of the matter is that this kind of information enables sellers to reach a vastly broader audience of those who resemble their most profitable customer segments.

Using tools like Facebook’s Custom Audiences, Twitter’s Tailored Audiences, LinkedIn’s Matched Audiences, and Google’s Customer Match, retailers are capable of targeting customers or prospects who have provided information such as their email address.

Naturally, this enables sellers to target those who are already familiar with the brand, hence more likely to convert. However, where the first-party data becomes extremely useful in expanding a retailer’s reach is that–using features like Custom Audiences–marketers can then build targeting lists for those who display similar characteristics as the previously uploaded customer list.

For instance, features like Google’s Similar Audiences can be used to find people with similar search behaviors and characteristics as those on the merchant’s first-part list. Similar Audiences can be established using a seller’s standard audience lists that have been uploaded to their Google Ads account. From there, Google will go to work finding folks who resemble those in the merchant’s list.

As Google states on its Similar Audiences for search page:

“Google Ads looks at the recent search activity of the visitors in your remarketing list to help aggregate search behavior of the visitors in your list.  Based on this information, the system automatically finds new potential customers whose search behavior is similar to that of people in your remarketing list… Your similar audiences’ lists will automatically get updated as the original list evolves and people change their search activity. So, you don’t need to update the similar audience list after it gets created.”

The expanded reach that these features (combined with first-party customer data) can provide to merchants is immense. Between targeting a more relevant audience and expanding the brand’s reach to those who mirror consumers who went on to convert, sellers can create incredibly profitable PPC campaigns.

Use Offline Conversion Data for Smart Bidding

Turning back to Smart Bidding strategies for a moment, it is important that retailers learn to use offline first-party conversion data to feed to Google’s algorithms to enhance campaign outcomes.

For instance, if sellers are optimizing their campaigns for conversion value, then it stands to reason that merchants will want to ensure that the values being given to Google are highly accurate.

However, as noted earlier in the piece, Google does not track important business data, such as the value of a prospect who converts with a sales rep over the phone. This is vital data to possess, as phone calls can often result in high-value sales for brands. However, if that value is not captured by Google, then campaign conversion values are likely to be askew.

However, by utilizing call tracking tools, merchants will be better equipped to harvest and feed Google data on critical targeting aspects such as:

  • Lead quality
  • Sales generated via phone calls
  • Value of sales earned

As opposed to basing goal values on sales team conversion averages, retailers can enhance their data’s accuracy, thereby elevating the accuracy of Smart Bidding decisions.

Enhanced Campaign Personalization

One of the greatest aspects of using data for eCommerce search and shopping optimization is that first-party data gives sellers insights into how to better personalize ads and their messaging for particular users.

The data that merchants collect from their website visitors provide a window into their wants, needs, and interests, thereby enabling retailers to serve up experiences and adverts that are relevant to the individual. Moreover, employing tools like Google Optimize, Optimizely, and others, sellers can continually refine their campaigns to get progressively closer to hitting the mark with target audiences.

The plain fact of the matter is that deeper knowledge about a customer base will always allow retailers to better refine their offers, messaging and campaigns overall.

Improved Feed Management

Google Smart Shopping campaigns have been getting increasingly popular among eCommerce retailers and marketers because of their ease-of-use and ability to produce results. Moreover, as droves of retailers were driven online as a result of the COVID-19 shutdowns, many were forced to learn digital marketing on the fly. Smart Shopping campaigns were undoubtedly quite useful for these folks.

With Google Smart Shopping campaigns, a retailer’s product feed is what Google uses to determine if, when and where a Shopping ad should surface. Therefore, product feed optimization is a critical component to succeeding with this ad type.

Getting set up to run Google Smart Shopping campaigns requires that sellers establish a Google Merchant Center account, integrate it with their eCommerce store, set a campaign budget, prepare their assets, inform Google on the country of sale and carry out other basic tasks.

Afterward, Google will pull information from the retailer’s product feed and experiment with different permutations of ad copy and images based on what was provided. Google will then show the most relevant advert on Google and its network of properties and partners.

However, merchants can go above and beyond by manually optimizing their product feed. Doing this will enable retailers to access targeting opportunities by making products more relevant to certain consumers.

For example, by optimizing product titles and descriptions, retailers can include keywords that will help to ensure that popular products reach specific customer segments.

However, in order to achieve this, retailers must know which keywords have proven fruitful for generating conversions and which customer groups bought from the brand after clicking on one of their ads. Fortunately, this information can be found in Google Analytics.

Final Thoughts

When using data for eCommerce search and shopping optimization, it is important to understand that things are changing. As a result of recent developments, third-party data is no longer enough.

Instead, many are turning to first-party data as this kind of proprietary information (in many cases) presents sellers with unbounding potential for achieving success with paid search and shopping campaigns.

The fact of the matter is that with regulations like the GDPR and CCPA coming into existence, the online advertising landscape is changing. As a result, most forward-thinking marketers are aiming to increase their reliance on first-party data above all other forms.

By using first-party data to uncover customer wants, needs, interests, concerns and other aspects of identity, merchants can successfully build out data resources that serve as the lynchpin for how the company engages customers across its website, email campaigns, social media platforms, call centers and all other touchpoints.

However, while there is great power to be found in the usage of first-party data, the challenges covered in this piece (and many others) still exist. Learning to aggregate, integrate, analyze and produce actionable insights from first-party data is not something that happens overnight and will require a significant investment of time, energy and resources to achieve in any meaningful way.

That said, given the importance of using first-party data in the coming era of digital marketing and eCommerce, merchants should consider partnering with an agency who can aid in helping to bring all of these pieces together into a coherent whole.

If your brand wants to prioritize leveraging first-party data for generating more profitable PPC campaigns, then reach out to Visiture’s paid media and advertising experts.

Our team of skilled eCommerce advertisers can help your brand to pull its first-party data together into a single location where it can be studied and successfully used to elevate the company’s paid search and shopping campaigns to a new level of performance and optimization.

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