Digital Guide to Navigating Healthcare and Pharmaceutical Marketing

Healthcare and pharmaceutical marketing is a complex landscape. A long-standing emphasis on in-person rep sales and difficult to navigate privacy laws have made the industry slower to adopt new marketing technologies and trends relative to other industries. 

This guide aims to debunk the uncertainty surrounding healthcare and pharmaceutical marketing best practices and provide a clear roadmap to creating a best-in-class digital strategy for your brand or the brands you partner with. 

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Understanding Implications of the Cookieless Future

“Businesses and advertising professionals will need to better understand how customers make decisions, what actions are valuable for businesses and bring that all together when showing success.” – Maggie Gotszling

Google’s announcement that Chrome will no longer support cookies as of 2023 has many digital marketers concerned about their future. Marketers that have historically relied on cookies to reach their target audiences and measure success will be greatly affected by this change and many are actively working on the next steps to avoid campaign performance declines. The actions taken by marketers in this pre-cookieless environment will help to shape and define the future of targeted advertising and performance metrics. 

Why are cookies important and how do they work?

Cookies are a backend line of code on a website that helps advertisers track a user’s behavior across the internet and includes 3rd party tracking pixels from platforms such as Facebook. The tracking of these activities makes it possible for advertisers to effectively deliver ads to their target audiences and directly measure and attribute conversions. With the deprecation of cookies, that tracking will no longer be viable, effectively blinding some targeting and measurement capabilities on which many marketers currently rely.  

What does it mean for campaign targeting strategies?

The major impact will be on retargeting third-party cookie-based audiences. It is recommended that advertisers begin shifting overreliance on this tactic and begin testing alternative targeting options to fill the gaps. Gathering first and second-party data (which is owned by publishers) will be central to an effective digital market strategy in a post-cookie environment. Additionally, the use of contextual targeting does not rely on cookies and provides brands with a strong opportunity to be able to generate increased brand awareness when done strategically. As an additional benefit, the cost of contextual advertising tends to be substantially lower than addressable impressions as data is not layered on, though costs are impacted by whether the tactic is targeted through a whitelist or contracted with a private marketplace deal.

Definitions and tips for collecting zero, first, and second party data

Zero party data: Coined by Forrester, Zero-Party data is collected when “a customer intentionally and proactively shares with a brand. It can include preference center data, purchase intentions, personal context, and how the individual wants the brand to recognize [them].” 

How to collect Zero Party Data:

  • Surveys
  • Polls

Tip: Don’t ask for too much too often and create poll fatigue on the consumer.

First party data: Observed behaviors of users who interact with your company. 

How to collect first party data: 

Form submissions or other forms of contact sharing on

  • Mobile apps 
  • Websites 
  • Social media 
  • SMS 
  • Email
  • Customer service platforms
  • Point of purchase

Second party data: Second Party Data is First Party Data collected by one company that they privately share with another company. For instance, when a publisher allows another company to use their CRM data to reach a target audience that overlaps with their own. An example of this would be if a brand were to work with Drizly, an online alcohol retailer, to reach their target audience of active digital alcohol shoppers. 

“Brands need to reestablish expectations for programmatic and be open to experiment with alternative targeting and measurement solutions. Ideally, this will happen in 2022 while we still have access to data that is likely to be lost.” – Savannah Westbrock

What impacts will we see on measurement?

Cookies have been the underpinning for most digital marketing performance measurements for over twenty years, including post-click and post-view conversions and attribution for sales impact. For example, the Facebook ecosystem will be heavily disrupted in attribution of conversion-based events, largely due to their reliance on mobile ad IDs for measurement. Historically, marketers have leaned heavily into Facebook and other walled garden environments due to their ability to evaluate strength ROI based on the multiple touchpoints that go into a final purchase, facilitated by the placement of a tracking pixel on the brand’s website. 

However, these walled garden pixels are defined as a third party cookie and will be limited in their ability to pass back data once the elimination of the cookie is mobilized. As a whole, we can expect  campaign performance on the front end to decline as compared to previous years, even if the backend business performance remains the same. Brands and teams should start to plan for shifts in attribution and performance as we get closer to the 2023 depreciation.

Fortunately, there are potential workarounds. For example, brands can overlay their conversion-based data found on Google analytics to match up on site conversion with Facebook mobile IDs after the fact. This helps level media metrics back up to business goals, but requires more analysis and less “real-time” results. Tests and conversations in 2021 can prepare in advance for performance declines and reduce a sense of panic. 

Post-cookie ID-based solutions for targeting and measurement

There are also multiple cookie alternatives in development that promise to bridge the addressability gap that will be created when cookies are deprecated. Here are a few of the options currently out there or in development.

Google’s Federated Learning of Cohorts (FLoC):

Google is working on a solution for targeting that groups internet users into groups, or “cohorts,” based on their browsing behaviors instead of giving each individual their own identifier. Advertisers can then target the group at large based on their shared interests as a whole. There are concerns that while this group-based option solves the privacy problem created by cookies, it will open the door for other privacy issues and could also lead to discriminatory, behavioral-based targeting. 

Standard Universal IDs: 

Originally used as a way to combat mismatched data when syncing cookie data across domains, companies like The Trade Desk, LiveRamp, and IAB have developed what are known as Universal IDs. This standardized identifier allows advertisers to buy into a community of shared data to track audience activity across the internet. The primary concern with Universal IDs, however, is that they still currently rely on third-party cookies, without which they are unable to set or recognize identifiers across domains. 

Encrypted Universal IDs:

Understanding the original design of Universal IDs would no longer be effective once cookies were depreciated, companies like LiveIntent (nonID) and The Trade Desk (Unified ID 2.0) started developing encrypted identifiers using email addresses instead of cookies to track user activity. The primary hurdle with email-based IDs is that they require users to provide and consistently use the same email across websites in order to build an accurate profile. If the user is unwilling to provide that data, or different emails are used for different sites, advertisers will be blind to their activity and be unable to target them accurately.

While all of these solutions have their pros and cons, they are all worth monitoring as they continue to develop as they will be key in building targeting and measurement strategies in 2023 and beyond. 

Recommendations to prepare for the cookieless future

  • Plan early & anticipate impacts to your measurement/attribution system. We encourage everyone to have conversations with their clients and agencies to set expectations ahead of time. We’ve outlined a quarterly look at the impact across audiences, e-comm/attribution as well as media mix & creative. 
  • Benchmark your current performance: You can start modeling the impact of third-party cookie blocking by recording your current analytic metrics and monitoring them as the update takes effect. Establishing benchmarks by operating system and browser will enable you to calculate most accurately the potential impact.
  • Apply business intelligence models to your analytics: Predictive analytics can be used along with your data to provide deeper insights for the best performing marketing tactics and identify macro and micro trends that influence your business outcomes.
  • Consolidate media activation to as few platforms as possible: Platforms are developing their own internal frameworks to accurately track and measure marketing performance outside of third-party trackers. The more platforms you execute your media through the more disparate measurement systems you have to take into consideration. There is also the likelihood that you will have duplication across platforms and consolidation will reduce that occurrence. 
  • Expand implementation timelines: Relying on first party data more and needing to run that first party data through an identity solution and then back into a web environment will add time to campaign and ad ops setups. While match rates should improve, campaigns will be moderately more cumbersome to set up, especially as we get used to these new flows. Teams and clients should build in extra cushion.
  • Create new relationships with third-party, cookieless data providers: This is not a new risk in the ad operations system, but an ever present risk that doesn’t go away under a new system. Fortunately, these companies benefit from interoperability and scale. The most important thing brands can do to reduce dependencies is to understand how your audiences and targets are built in each platform and know what’s different depending on the partner. Always ask what’s inside the box or model.

“Brands who have been targeting super-niche audiences will have to reestablish expectations for programmatic and be open to experiment with alternative targeting and measurement solutions. Ideally, this will happen in 2022 while we still have access to data that is likely to be lost.” – Colin Duft

Reaching Your Ideal Audience in a Cookie-less Environment

As the end of the third-party cookie nears, at the forefront of many marketers’ minds is the concern that approaches to audience targeting will soon be reversed by ten years and limit the sophistication of their data-focused strategies. While those who have solely relied on cookie-based audiences and retargeting audiences are going to need to overhaul their execution, many data technology partners have alternatives that will help bridge the gap with innovative solutions and, perhaps most importantly to the industry, this will require a necessary reset to marketers’ and brands’ overreliance on retargeting and vanity metrics.

ID-Based Solutions

With the elimination of cookies, targeting solutions that are based on anonymized PII is going to be critical to maintain the one-to-one approach to reach consumers. Many of the upcoming ID-solutions will be interoperable, meaning they will speak to one another and create synergies for marketers. Below are a few of the most discussed solutions across the industry:

Unified ID 2.0

Many publishers and technology partners are working together to be able to produce Unified ID 2.0, which will be an open source solution built with hashed and encrypted email addresses across the web where a user has logged in. This solution, initially spearheaded by The Trade Desk and now being overseen by Prebid, has gotten significant backing by other publishers and brands. This includes, but isn’t limited to, Index Exchange, Magnite, PubMatic, OpenX, SpotX, LiveRamp, and The Washington PostFor consumers who are wanting to have more transparency about how their data is being used, they are going to be able to monitor and adjust how their data is being leveraged and encourage publishers to be more forthright in the value exchange that occurs. 

Liveramp Authenticated Traffic Solution

Similar to Unified ID 2.0, Liveramp is developing their own methodology to also get ahead of the cookieless future in collaboration with their partners. As outlined on Liveramp’s website, their “IdentityLink unlocks the value of your data securely because it’s encoded for every identity space, protecting your data from loss and misuse.” However, it does differ from the unified ID solution because it does not include identifiers such as fingerprinting and hashed emails. Instead they are creating an environment known as “Safe Haven,” which will aggregate many data providers’ information and enable for next-level machine learning to grow customer understanding and activate against new audiences. This will allow for fragmented data to be assimilated into a people-based solution based on identity across channels.

Lotame Panorama ID

Lotame’s solution is people-based and compliant, accumulating inputs across the web, mobile, connected TV, and customer data. This data can then be utilized across devices, domains and platforms universally across the open-web. As outlined in their press release, Lotame “…[matches] attributes across devices and domains to an individual…[leveraging] more than 90 platform partners, plus data from 180 providers in 58 countries.” This allows the ID to scale.

Neustar’s Fabrick ID

Neustar recently announced that they would also be rolling out an ID which aligns with the customer cloud solution that was released in the summer of 2020.  According to AdExchanger, “…Neustar has an API that publishers can call with the information they have on customers, most likely a hashed email or phone number. Neustar then spits out a token (the Fabrick ID), which publishers can use to share identity data back with Neustar’s advertiser clients and to sell their media programmatically on the open exchange.” Steve Silvers, the SVP of product and GM for customer experience at Neustar, informed AdExchanger that the ID is a more privacy compliant solution as compared to third-party cookies because it expires after 7 days.

First and Second-Party Data

First and second party data have been highly valuable for brands for a long time. Targeting these audiences allows for more touchpoints with known prospects, the ability to continue touchpoints beyond email with past customers, an opportunity to upsell with other relevant products, and the luxury of using other companies’ powerful audiences in your targeting. While historically important, this data is expected to be essential to establishing a well-rounded digital strategy in a post-cookie environment. The companies that are poised for success here have been building deterministic identity graphs for years not only based on logins and emails, but also devices, purchase information and phone numbers.

The Benefits of Walled Gardens’ Second Party Data

While there has historically been some frustration across marketing professionals on the siloed effect of walled gardens, marketers are beginning to change their tune after realizing limitations that they will be confronted with once the deprecation of the third-party cookie is in full-swing. The great thing about these providers is that nearly everyone on each platform is signed in, meaning that there is inherently an ID present without the need of cookies. Now that doesn’t mean there will at least be some impact on scale with data transparency really coming to the forefront in 2021, but there will still be an opportunity to reach deterministic audiences based on their behaviors. Coegi will have a follow-up piece all dedicated to walled gardens – the good, the bad, and the ugly.

Cohort-based Audiences

Some partners, like Google, are turning to Federated Learning of Cohorts, or FLoCs, to generate audiences. This is basically creating an audience clusters based on common interests. These interests are determined based on past browsing history online, but also eliminates any IDs associated with the targeting, which provides more privacy while also allowing marketers to ensure they are able to provide relevant content to their consumers.

Advanced Contextual Targeting

Contextual-based targeting centered around keywords has been implemented across programmatic campaigns for years to expand prospecting pools and assume relevancy. While this seems overly simplistic given the granularity of other targeting options, it actually offers a great opportunity to reach those whom you might have not otherwise considered to be part of your target audience and also expand reach through cost-effective CPMs. Furthermore, contextual targeting has come a long way since the early 2010s, and many data providers now offer unique solutions based on real-time data and artificial intelligence that elevates the sophistication even further and allows for greater personalization in marketing.

One such solution is offered by Peer39, a highly regarded contextual data marketplace, who recently partnered with multiple data providers including Newsguard, Hotspex Media, and Planalytics. They are now rolling out a solution that allows for contextual targeting layered with weather triggering events, known as the product demand index, which takes into account environmental factors and dynamics weather conditions in the location that the user is. Beyond this, they also allow marketers to select contextual placements based on credibility and brand sensitivity of the webpage, overall emotional sentiment, and predictive trending targeting based on topics that are relevant to the brand.

Another respected contextual data partner, Oracle (who bought Grapeshot back in 2018), also offers a contextual intelligence opportunity. By using sets of keywords and phrases, Oracle Grapeshot is able to understand relevancy of the page for the category of content and subsequent strength of the category match. This approach allows contextual targeting to be evaluated on a broad versus niche basis, offering a variety of options for brands to tap into. 

Semasio also has a keyword-based contextual option that identifies webpages’ most significant terms and phrases and categorizes accordingly, inferring meaning and relevance. However, one of its more interesting solutions is the seed-based audience. This approach takes key customers or contacts from a CRM, analyzes what semantically differentiates this audience from the broader population, and produces a lookalike model of sorts based on contextual engagement. 

These elevated approaches open up new opportunities for marketers to intelligently lean into contextual.

What It All Means

As a whole, marketers and brands are going to have to tap into creative solutions to tap into audiences they have been targeting. While it will be time consuming to build up the repertoire needed, it is ultimately a safer direction to protect consumers and build trust.

Building and Leveraging First-Party Data

What is first-party data?

First-party data is information collected directly by website publishers about their site visitors or customers and is stored in a customer-relationship-management (CRM) database. First-party data typically includes personal information like names, addresses and phone numbers. It can also include site-interaction data, which is highly informative when it comes to tracking product and services purchases or purchase intent, and is a key component of audience targeting for any marketing strategy. While retargeting strategies are often very effective, building and leveraging first-party data has many additional use cases. Coegi helps agencies and brands create customized strategies for capturing, onboarding and leveraging first-party data for more effective one-to-one communication with audiences.

Building your first-party database.

Coegi develops a customized a pixel strategy for each client to build or grow their first-party database. Generally, a pixel is placed on a website’s home page to collect information about site visitors, and conversion pixels can be placed on other pages or site buttons that indicate increased interest or intent. Usually this will be a lead capture form, checkout button or a page view of a specific webpage that assists the advertising end goal.

Coegi’s partnership with LiveRamp enables companies to onboard first-party data and make it available to use in programmatic and social platforms. Part of the data onboarding process is anonymizing personally identifiable information (PII)  to protect consumer privacy. Another key step involves matching offline data to online devices, such as a desktop browser cookie or mobile device ID and social media profiles1. Agencies, publishers, and brands partnering with Coegi can access the full capabilities of LiveRamp data onboarding and activation services at a cost commensurate with the volume of client units available to them. After uploading first-party data, like a CRM list, your data can then be leveraged to create audience models and a retargeting strategy.

Leveraging first-party data.

Collecting first-party data on who has interacted with your ads or visited your site allows you to implement a retargeting strategy. Generally, retargeting provides the best performance. These users are aware of your product or service and are likely in-market for purchase.  

Additionally, onboarded data can be modeled and segmented within platform DMPs to create unique audiences for prospecting campaigns.  Audience segmentation allows you to segment out various groups for a more personalized experience, rather than serving a generic ad to an entire prospecting list2. Furthermore, look-a-like audiences can be constructed as a way to reach new people who are likely to be interested in your business because they exhibit similar online behavior to your existing customers.

More than just retargeting.

As marketing becomes a more complex one-to-one communication process, advertisers need to reconsider how the process of onboarding first-party data is incorporated into their campaigns1. While retargeting strategies will remain a key component of digital marketing, never underestimate the power of audience segmentation and personalization when it comes to reaching your audience.

Reaching Your Audience Through Television

Television has long been a desirable medium for brands to have extensive reach across their audiences, building awareness and increasing share of voice. It continues to be very powerful with over 245 million TV viewers in the U.S. according to eMarketer who watch live or recorded video on a set. However, the television landscape has seen many shifts in the last few years in particular, as consumers share their time between linear and streaming services, in addition to other forms of digital video on social platforms. Today, there are over 213 million connected TV viewers in the U.S., and it’s poised to continuously grow to over 230 million ahead of 2025. As a result, Marketers need to be planning their television buys with a holistic approach, understanding that the only way to have comprehensive audience reach is to tap into both linear and connected television channels and using a measurement partner to understand impact and incrementality. 

Why Neither Linear Nor Connected Television Can Be Ignored

According to The Trade Desk’s “Future of TV” report, 47% of U.S. TV viewers are already cordless and another 42% plan to “cut the cord” or minimize traditional television spend within the year. That being said, the scale that continues to be achievable on linear definitely makes it a channel that should continue to be leveraged. There are always going to be some consumers who choose to exclusively view on linear, as well as consumers who exclusively use streaming. This means that both channels must be incorporated into media plans to ensure you are reaching your target audience in a non-skippable environment where your brand message is showcased.

Another major reason that brands who have traditionally used linear television are now looking more heavily into connected tv is due to the incrementality. In fact, according to eMarketer this is the second most common reason that this tactic is deployed apart from targeting capabilities. This approach has worked well for many brands, including Hershey who saw the consumer trends and understood the need to act. This extends beyond Amazon to other OTT/CTV like Hulu, Roku, Tubi, Discovery+, and more.

How Can We Evaluate Success on Cross-Channel TV

There are measurement partners in the space that are able to go beyond number of impressions or gross ratings points to understand how television advertisements are impacting the bottom line. This can be achieved through tools such as lift studies that can interpret lift overall brand awareness and as well lift in conversions, whether that is site visitation or actual purchases. In the world of the pending deprecation of third-party cookies and iOS 15, attributing business results to media channels is going to become more challenging. Fortunately, television is not dependent on cookies and is poised to become an even more valuable channel for marketers to lean into.

Best Practices for Targeting in Pharmaceutical Campaigns

What is first-party data?

First-party data is information collected directly by website publishers about their site visitors or customers and is stored in a customer-relationship-management (CRM) database. First-party data typically includes personal information like names, addresses and phone numbers. It can also include site-interaction data, which is highly informative when it comes to tracking product and services purchases or purchase intent, and is a key component of audience targeting for any marketing strategy. While retargeting strategies are often very effective, building and leveraging first-party data has many additional use cases. Coegi helps agencies and brands create customized strategies for capturing, onboarding and leveraging first-party data for more effective one-to-one communication with audiences.

What does this mean?

The first step in determining targeting capabilities for your brand is to understand if the brand falls under the ‘sensitive’ category. According to the NAI, there are two subsets of sensitive information: 

  1. Data about a health condition or treatment derived from a sensitive source 
  2. Data about certain sensitive conditions regardless of the source of the data

Determining whether a health condition is considered ‘sensitive’ is unclear in the industry. The NAI provides only a few categories that define as sensitive which include drug addiction, sexually transmitted diseases, mental health, pregnancy termination, and all conditions predominantly affecting or associated with children not treated by OTC and Cancer.

There are resources to help guide the analysis of determining whether the brand falls into the sensitive category. The NAI provides a multi-step guidance for members on their best practice to help determine whether any targeting efforts or data segments are considered sensitive.

However, this guidance does not give advertisers a clear list of the targeting capabilities that are compliant. Coegi recommends to use the guide to help drive direct conversations with the client in coming to a mutual agreement on whether the brand falls into either the sensitive or non-sensitive category to influence targeting solutions that are compliant. 

Because there is no clear list provided by any regulatory source, Coegi recommends working with the client to align on the brand’s definition of sensitivity as this will greatly affect compliant targeting capabilities. 

The Trade Desk (a member of the NAI) also takes precautions and has implemented a healthcare policy to ensure all targeting efforts are safe. Because there is no official, comprehensive list from the NAI to deem health conditions sensitive or non-sensitive, The Trade Desk has its own process in defining whether a condition is deemed high, medium or low in the sensitive category to see what targeting capabilities are permitted for each brand. This policy uses a multi-factor analysis to take into account many considerations when calculating each condition’s category. 

Other advertising platforms have similar protocols for brands in the healthcare space. Before running paid ads through Facebook, advertisers must apply for permission according to its Promotion of Prescription Drugs policy and first gain approval from Facebook.

How to Approach Targeting a Pharmaceutical Audience

Once alignment on whether the brand falls into either the sensitive or non-sensitive condition category is achieved, below are the different ways to target both consumers and HCPs within the pharmaceutical vertical: 


Behavioral Targeting

  • This form of targeting is typically not a compliant way to reach a consumer given it’s ‘data about a health condition or treatment’. However, there are third party data providers that use de-identified information which is considered compliant according to the NAI. 
  • It is critical to understand how the data is being collected if using any third parties to reach a patient audience. Coegi will always do a detailed analysis to determine whether a data provider is compliant according to industry best practices. 
  • From a blog post by Yeehooi Tee of PulsePoint, not all audience models are created the same and there are key factors to understand when evaluating health data segments. These factors include the source of the seed data, the attributes used to model the data, understanding the seed to output ratio and among many other factors. 

Contextual Targeting

  • There are no known regulations for using contextual targeting for a consumer audience. This is a popular approach in reaching a patient and caregiver audience in a compliant manner. 


  • For both sensitive and non-sensitive conditions, geo-targeting a consumer audience is not compliant. According to the NAI, unless the user’s opt-in consent is given to target by precise location data (like a health care provider’s office), this form of targeting falls outside of best practice.  
  • While using precise location data requires opt-in, there are other forms of targeting that could reach a patient audience using geographic data. This data would need to be further vetted to ensure it’s not precise location data. 


  • According to the 2020 code, retargeting is a form of Tailored Advertising. For sensitive health segments, an opt-in consent is required from users in order to retarget a consumer audience. 
  • Even for other non-sensitive health segments, Coegi still recommends having a conversation with the brand team to gain alignment prior to executing this form of targeting.

For Healthcare Providers

Because you’re targeting by profession, there are fewer restrictions when trying to target a HCP audience (while still using de-identified information). It’s an industry norm that an audience-first approach in reaching HCPs is best practice and compliant. 

Various forms of audience targeting for HCPs can include: 

  • Dx Targeting – ICD-10 code for specific diagnosis 
  • Rx Targeting – prescription code for specific drugs  
  • Specialty Targeting – target HCPs by specific medical specialty
  • List Match Targeting – target HCPs by specific NPI number

Depending on a particular client’s goals, Coegi will provide a recommended targeting strategy to reach a HCP audience 

However, even with it being less restricted, Coegi still recommends investigating and understanding the source of the data segments associated with NPIs and still having a conversation with the brand team to gain alignment on certain targeting efforts especially forms of retargeting.


Written by: Colin Duft, Account Strategy Director

Why is an Audience-First Strategy Important?

When it comes to digital media planning and strategy, it’s easy to get absorbed by a channel-driven approach. For example, many marketers understand that Connected TV serves as a strong upper funnel tactic for incremental reach, that social yields engagement making it a good fit for the middle funnel  and that display retargeting will drive more bottom funnel goals. However, this causes campaigns to quickly turn from strategic to tactical, causing an overall disconnect. Instead, marketers should leverage an audience-first approach that first determines who their most valuable customers are, where they are most likely to interact online, and how we can best reach them through an omni-channel strategy.

What is an Audience-First Approach?

At the end of the day, increased brand awareness, consideration and sales all come down to one thing: customers. Without them, brands aren’t able to achieve their business objectives. Therefore, we believe that digital media strategies need to place audiences at the cornerstone of their planning.

Once the target audiences are identified through industry and vertical research, evaluation of personas and analysis of current customers, operations teams are able to use data sets (1st, 2nd and 3rd party audiences) available across the various platforms to reach their audiences, only selecting to activate on channels where these audiences are known to engage and available to target. This approach provides meaning to why specific channels are selected over others and ensures that the strategy is based on how the brand can best achieve their goals.

But perhaps most importantly, the focus should be on reaching people, not devices.

As we are beginning to be confronted with the realities of a cookie-less world, we can be confident that we will continue to be able to deliver robust targeting strategies through:

  • Mobile ID matching
  • 1st party data/CRM and lookalike modeling
  • 2nd party data
  • Keyword targeting
  • Category/contextual targeting
  • Deterministic 3rd party segments based on PII

What Does This Mean for Coegi?

At Coegi, we always believe in an audience-first approach. To best achieve our client’s objectives, we assemble the best strategies, tactics, and channels to deliver streamlined marketing to the target audience using our best-in-class technology stack.

We are consistently using AI, machine learning, and human intuition to delve into the data to identify which audiences are working, which channels are driving the best results and making optimizations to create media efficiencies for our clients in an ever-changing environment.

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