The value of building relevance relies on a single principle i.e., an advertiser can use advanced analytics to reach more consumers by delivering the shopper-significant ads through the right channel and at the right time. With the capability to test and learn. It is achieved by leveraging first-party data and providing tailored and meaningful ads to the shopper. The depth of the data around shopping and purchase behavior leads to predictive patterns that deliver the ROI advertisers will pay.
In retail media, highly relevant ads are displayed by showing product ads based on what shoppers are looking for while tightening consumer privacy standards. Governments and tech companies have undercut long-standing digital-marketing tools like third-party cookies, which makes it more challenging to communicate with consumers in personalized ways and gain attention in a crowded marketplace. Retail media fills this void, it enables retailers to access first-party data and “closes the loop” by identifying those who purchase after seeing an ad making retail media a compelling new channel for advertisers..
Online retailers have realized that contextual user targeting helps them deliver quality shopper experience. Let’s have a closer look at how it ensures relevance.
Retail platforms hold enormous amounts of first-party data that is analyzed to comprehend shopper experiences and push tailored ads for higher engagement. An ideal retail media platform processes search phrases, keywords, and product categories to their core meaning and maps them with advanced tech tools like ML and NLP. Additionally, user profiles are outlined based on signals identified in their purchase patterns and site activity, such as purchases, location, search history. It creates a better means to deliver contextual user-targeted ads for online retailers without intruding on their shopper’s privacy.
Identifying sections or pages where users spend most of their time and unlocking ad spaces on those sites to deliver contextual user-targeted ads.
Utilizing the web page for showcasing ads better will help the user experience and boost engagement with them. A great UX ensures all points of interaction are positive for a user. It also includes good usage of ad inventories. These spaces can not be used for running awareness-based ads only but also to show product ads to nudge the shopper to make a purchase.
Running ads will not make an impact if the process is not engaging and lagging. Latency results in poor shopping experiences and it is more likely to happen when your website is already processing large amounts of data. Retail media platforms like Monetize, ensure that the latency timing is brought under 50ms. To ensure the relevant ads are getting results, online retailers need to keep their shoppers in the loop, and make quick adjustments on the retail platform
Customer privacy has been one of the most sought-after issues in the digital media landscape, e.g., the scrutiny of third-party for lax security standards led to its demise. Contextual user targeting offers a new way, as retail media accesses the data in an encoded format, which prevents them from hyper-targeting individuals. The audience is targeted based on the aforementioned signals. Hence, there is no data leakage and breach of shopper’s privacy.
Building a retail media platform comes with its share of challenges, here are some:
It takes massive inputs of time, labor, and bandwidth to develop an engine that can track, differentiate, and process large volumes of data to churn out resourceful information. Creating a tech stack that helps retailers understand consumer behavior, trends, and segmentation to provide comprehensive and curated responses.
An enormous investment goes into creating a sophisticated platform such as this, which may or may not bear results.
for everyone involved in online retailing, as it is one of the driving factors behind consumer engagement with the website in the first place. The safety of the shopper's identity is ensured by encoding the data. This encoding leads to no breaches of the user's privacy.
is an uphill challenge for retailers to claim. Establishing a retail media platform to deliver ads by using first-party data is not that simple to build. Retailers will have to create separate interfaces for themselves and the advertisers, provide analytics across various attributes, make integrations, and much more.
Online retailers are sitting on a gold mine of data. But to extract the said gold takes a lot of effort and expertise. Establishing an in-house retail media platform includes developing a platform powered by AI and ML that will help an online retailer to simplify how the 1p data is processed to generate profitable ads. Things like thorough behavioral analysis of the shopping and purchase data and predictive patterns.
Monetize by Onlinesales.ai, is a state-of-the-art retail media platform that helps online retailers deliver ads and maintain a consistent source of revenue. A platform powered by AI and ML, which helps in indexing and mapping keywords, products, and categories. It is capable of processing large amounts of data from online retailers and segments it into easy-to-determine and act upon signals instantly, as Monetize has a latency of less than 50ms. Monetize offers intuitively designed dashboards for retailers and their advertisers that enable them to monitor their ad performance. It is easy to use and quick on integration.
Looking for ways to leverage your first party data and traffic to earn additional revenue? Our AI ML powered retail media tech, Monetize, helps you enable every advertiser to run ads on your platform to achieve their marketing goals and ensure higher yields for you. To learn more, contact us today.
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