MARKETING
8 Factors to Consider Before Buying or Building your AI Solution
Artificial intelligence (AI) – it’s here, it’s there, it’s everywhere. Businesses in every vertical – retail, finance, healthcare, manufacturing, transport, supply chain, entertainment, and technology – use AI.
More than a quarter of companies using AI attribute at least 5% of their earnings before interest and taxes to AI. Almost two-thirds of early AI adopters note AI gives them a competitive advantage. Given the benefits, it’s hardly surprising that some businesses have FOMO on AI.
But when the company is ready to adopt AI, they face a dilemma – should they buy or build? Read on to learn about factors to consider when deciding on AI solutions for your business.
AI for business
Startups and big enterprises ready to adopt AI have two ways to go about it: Build their own AI model or buy commercially available AI software. Both options involve the use of open-source AI or off-the-shelf product such as free live chat apps
Before dissecting the build vs buy dilemma, it’s important to understand open-source and proprietary AI software.
Open-source AI
Open-source AI includes freely available AI tools. These could be algorithms, datasets, ready-to-use application programming interfaces (APIs), libraries of codes, or a combination of all. Some of the free AI and machine learning (ML) platforms are Tensorflow, Python, PyTorch, KNIME, Apache Spark, and H2O.ai.
Usually, each AI software has specific use cases like speech recognition, computer vision, ML, natural language processing (NLP), or big data analytics. For instance, TensorFlow and PyTorch are suited for building ML and deep learning models. Libraries like Keras and OpenNN, on the other hand, are artificial neural network (ANN) frameworks. Businesses leverage these libraries and platforms to build their own AI system based on their requirements.
Commercial AI software
From chatbots and conversational AI to automation and advanced data science, there are many ready-to-use AI tools. Though it’s costly, these tools can save a lot of resources and time for the company. The most common commercial model of AI software is the annual subscription model that includes necessary licenses, support, and service from vendors. Another type is “pay-as-you-go” where one can access the AI software as an API.
Major tech companies like Google, Microsoft, Amazon, IBM, and Salesforce also offer AI and ML as a platform service. These AI services provide end-to-end cloud-hosted platforms for developing and deploying AI models.
Breaking down the build vs buy dilemma
Imagine you need a new house – would you buy or build one? Choosing between the two depends on a lot of factors. What kind of house do you want? What resources do you have on hand? How much time and money do you have? And how much of each are you willing to spend?
Deciding on whether you want to build or buy your AI for your business is similar. Let’s look at the factors you should consider before taking the plunge.
The need: Why do you need AI?
Diving into algorithms and neural networks before figuring out what you want from AI is a bit like diving into the ocean to find a lost treasure that might or might not exist. What is your business looking to achieve by using AI tools? Is AI a core component of future business growth? Or is it to automate a task or improve business processes?
If AI is the core of your business, build it. If you want to use AI for just specific business operations, then buy. A chatbot provider needs to build its own NLP model. But a small online startup doesn’t have to build a huge NLP model to have a chatbot on its website. It can simply buy the tool from conversational AI providers like Dialpad or Drift and improve customer experience.
The difficulty: How complex is the AI solution?
The complexity of the AI solution the business is looking to adopt is also an important element to think about. There are many tried and tested products in the market that you can buy for common AI applications, like sales and marketing automation processes, predictive forecasting, chatbots, speech-to-text, or machine translation.
But sometimes, the data involved is sensitive or the business is looking for a novel solution. Commercial tools are simply not suitable or sufficient in these cases. Netflix, for instance, built its own proprietary AI model that offers personalized movies and shows recommendations based on user data. It was worth it to build because Netflix considers this feature critical to its business.
On the other hand, Woodside Energy, an oil and gas company, leveraged IBM Watson’s ML and NLP tech to make 30 years of data on oil platform operations accessible throughout the company. Woodside owns the data, but shared it with IBM to tap their expertise instead of building it in-house.
The human effort: Do you have the right people?
Evaluate the AI capabilities of your in-house experts. Can your pool of technical experts develop AI frameworks? Or does your firm have the resources to hire such experts? If yes, then the firm can think about building an AI model in-house.
Tech companies, AI vendors, and large enterprises in the banking, retail, and healthcare sectors have a huge pool of AI experts working exclusively on AI and have the resources to develop their solutions in-house.
Bank of America, for example, built its own virtual banking assistant, Erica. By the time the bank’s AI assistant was in the beta phase in 2017, the bank had a dedicated team of more than 100 people working on the project.
However, if the firm doesn’t have technical expertise or resources to hire, it’s best to purchase from a vendor. For example, a small marketing firm can buy an AI-powered content creation tool rather than investing millions to hire a team and develop it in-house.
The time: What’s the deadline?
Do you need the AI software immediately? Or can you wait to get a custom tool?
If your business needs the tool at once, and there are already multiple products available to purchase, then buying is the ideal solution. But, if the company needs a custom tool that needs time to build, the firm can develop on its own, given it has the resources to do it.
The cost: What’s the budget?
Many enterprises fail to understand the true cost of building or buying an AI model. Both options require heavy investment to get the right people, hardware, and software.
A company can cut some costs by building AI using free, open-source software. But there are other prices to pay. From getting training data to buying necessary software and hardware like cloud storage, expensive computing power, and AI operationalization software, there are significant hidden costs involved. Companies have to cough up more to hire (expensive and rare) AI experts. The average base pay for an AI job is easily above $100,000 in the USA.
Buying a third-party AI solution solves the problem of having to spend on hiring an AI team. But commercial tools can still be expensive. A custom AI solution can cost from $6000 to over $300,000 per solution while a third-party software can cost up to $40,000 per year. Firms will have to weigh the costs of both options and decide.
The integration: Can your current tech support AI?
It’s critical to gauge how well the existing IT infrastructure can integrate with AI, whether building or buying. The team should look at whether the AI platform can sync with their current tech stack. More often than not, open-source platforms have integration and scaling issues.
Commercial vendors take care of the dreaded task of AI integration, scaling, and compatibility issues. But it’s always better to check the compatibility of the vendor tool with the existing ecosystem. If you’re integrating an AI solution to optimize your lead generation process, it should seamlessly integrate with your existing CRM. Ignoring this can become costly to fix.
The service: What happens when something goes wrong??
With commercial products, there’s always vendor service and support. The AI vendor has responsibility and accountability for the smooth functioning of the tool. Your team can rely on them to fix bugs and other issues that crop up in the AI model. While building AI, the company has to deal with any issues that crop up without much support.
The security: Is your AI safe?
Both open-source and commercial AI platforms have potential security risks. Unlike popular opinion that open source has more vulnerabilities, nearly 90% of IT leaders think it’s as secure or more secure than proprietary software. So the question is not about which option is more secure but which needs more support. The answer is building with open source. AI vendors take care of security issues and fix bugs and patches themselves. But building AI in-house means having a team dedicated to looking at potential security issues. This adds significant costs to the budget.
Building vs buying AI: Weighing the pros and cons
Let‘s make your decision-making on AI solutions a little easier. Here are some common advantages and disadvantages of building vs buying AI.
Pros and cons of building AI
Building an in-house AI using open-source frameworks suits firms that have unique data and the capability to invest time and resources. Its advantages include:
- no or low-cost investment in the tech
- better customization based on needs
- control over both data and the model
- flexibility to change the model when required
- community support
However, open-source AI platforms have several gaps like:
- high turnaround time
- difficulty in hiring AI experts and data scientists
- lack of service and support to solve issues
- added security cost
- compatibility issues with other software
Pros and cons of buying proprietary AI
Buying an off-the-shelf commercial tool might be best for companies that don’t have the human resources to build their own solution or lack unique datasets. Its advantages include:
- specialized knowledge for a particular AI use case
- availability of large, well-organized training datasets
- seamless integration of AI tools into existing infrastructure
- ability to scale AI models
- continuous vendor service and support to solve issues
But commercial products have their own drawbacks like:
- high investment cost
- fewer customization options
- risk of losing access to critical data
- vendor lock-in periods
Still confused? Go for the lean strategy
If you’re still confused after assessing all factors, think about the lean AI strategy. The strategy comes from the Japanese manufacturing industries’ philosophy called the lean manufacturing process. Adopted by carmakers like Toyota, the strategy aims to reduce production waste without sacrificing efficiency and quality.
The lean AI strategy also aims for the same: implement AI incrementally while reducing resource costs and risks. The business can start with a small AI project that delivers a minimum viable AI product (MVAP).
The build-vs-buy decision tree
With MVAP in mind, consider the following decision tree. Scout for an available solution. If there are multiple commercial products, buying would be the best solution. If there are not many vendors offering the required tool, look for a partner to develop a custom AI solution. This saves the company time, efforts, and resources of building from scratch.
However, if both buying and partnering don’t work, the company can build its MVAP. Aiming at MVAP helps the company kickstart the AI project sooner. With established deadlines and goals, companies can assess the performance and business impact of MVAP faster. As the project matures, the business gets more opportunities to evaluate and undertake more ambitious AI projects.
Winning with AI
Like all deliberations about implementing new technologies, it’s important to make an informed decision on AI in your company. Whether you choose to build or buy your AI, just keep in mind that AI is not going anywhere anytime soon – so start early to reap the rewards early.
MARKETING
AI driving an exponential increase in marketing technology solutions

The martech landscape is expanding and AI is the prime driving force. That’s the topline news from the “Martech 2024” report released today. And, while that will get the headline, the report contains much more.
Since the release of the most recent Martech Landscape in May 2023, 2,042 new marketing technology tools have surfaced, bringing the total to 13,080 — an 18.5% increase. Of those, 1,498 (73%) were AI-based.

“But where did it land?” said Frans Riemersma of Martech Tribe during a joint video conference call with Scott Brinker of ChiefMartec and HubSpot. “And the usual suspect, of course, is content. But the truth is you can build an empire with all the genAI that has been surfacing — and by an empire, I mean, of course, a business.”
Content tools accounted for 34% of all the new AI tools, far ahead of video, the second-place category, which had only 4.85%. U.S. companies were responsible for 61% of these tools — not surprising given that most of the generative AI dynamos, like OpenAI, are based here. Next up was the U.K. at 5.7%, but third place was a big surprise: Iceland — with a population of 373,000 — launched 4.6% of all AI martech tools. That’s significantly ahead of fourth place India (3.5%), whose population is 1.4 billion and which has a significant tech industry.
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The global development of these tools shows the desire for solutions that natively understand the place they are being used.
“These regional products in their particular country…they’re fantastic,” said Brinker. “They’re loved, and part of it is because they understand the culture, they’ve got the right thing in the language, the support is in that language.”
Now that we’ve looked at the headline stuff, let’s take a deep dive into the fascinating body of the report.
The report: A deeper dive
Marketing technology “is a study in contradictions,” according to Brinker and Riemersma.
In the new report they embrace these contradictions, telling readers that, while they support “discipline and fiscal responsibility” in martech management, failure to innovate might mean “missing out on opportunities for competitive advantage.” By all means, edit your stack meticulously to ensure it meets business value use cases — but sure, spend 5-10% of your time playing with “cool” new tools that don’t yet have a use case. That seems like a lot of time.
Similarly, while you mustn’t be “carried away” by new technology hype cycles, you mustn’t ignore them either. You need to make “deliberate choices” in the realm of technological change, but be agile about implementing them. Be excited by martech innovation, in other words, but be sensible about it.
The growing landscape
Consolidation for the martech space is not in sight, Brinker and Riemersma say. Despite many mergers and acquisitions, and a steadily increasing number of bankruptcies and dissolutions, the exponentially increasing launch of new start-ups powers continuing growth.
It should be observed, of course, that this is almost entirely a cloud-based, subscription-based commercial space. To launch a martech start-up doesn’t require manufacturing, storage and distribution capabilities, or necessarily a workforce; it just requires uploading an app to the cloud. That is surely one reason new start-ups appear at such a startling rate.
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As the authors admit, “(i)f we measure by revenue and/or install base, the graph of all martech companies is a ‘long tail’ distribution.” What’s more, focus on the 200 or so leading companies in the space and consolidation can certainly be seen.
Long-tail tools are certainly not under-utilized, however. Based on a survey of over 1,000 real-world stacks, the report finds long-tail tools constitute about half of the solutions portfolios — a proportion that has remained fairly consistent since 2017. The authors see long-tail adoption where users perceive feature gaps — or subpar feature performance — in their core solutions.
Composability and aggregation
The other two trends covered in detail in the report are composability and aggregation. In brief, a composable view of a martech stack means seeing it as a collection of features and functions rather than a collection of software products. A composable “architecture” is one where apps, workflows, customer experiences, etc., are developed using features of multiple products to serve a specific use case.
Indeed, some martech vendors are now describing their own offerings as composable, meaning that their proprietary features are designed to be used in tandem with third-party solutions that integrate with them. This is an evolution of the core-suite-plus-app-marketplace framework.
That framework is what Brinker and Riemersma refer to as “vertical aggregation.” “Horizontal aggregation,” they write, is “a newer model” where aggregation of software is seen not around certain business functions (marketing, sales, etc.) but around a layer of the tech stack. An obvious example is the data layer, fed from numerous sources and consumed by a range of applications. They correctly observe that this has been an important trend over the past year.
Build it yourself
Finally, and consistent with Brinker’s long-time advocacy for the citizen developer, the report detects a nascent trend towards teams creating their own software — a trend that will doubtless be accelerated by support from AI.
So far, the apps that are being created internally may be no more than “simple workflows and automations.” But come the day that app development is so democratized that it will be available to a wide range of users, the software will be a “reflection of the way they want their company to operate and the experiences they want to deliver to customers. This will be a powerful dimension for competitive advantage.”
Constantine von Hoffman contributed to this report.
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MARKETING
Mastering The Laws of Marketing in Madness


Navigating through the world of business can be chaotic. At the time of this publication in November 2023, global economic growth is expected to remain weak for an undefined amount of time.
However, certain rules of marketing remain steadfast to guide businesses towards success in any environment. These universal laws are the anchors that keep a business steady, helping it thrive amidst uncertainty and change.
In this guide, we’ll explore three laws that have proven to be the cornerstones of successful marketing. These are practical, tried-and-tested approaches that have empowered businesses to overcome challenges and flourish, regardless of external conditions. By mastering these principles, businesses can turn adversities into opportunities, ensuring growth and resilience in any market landscape. Let’s uncover these essential laws that pave the way to success in the unpredictable world of business marketing. Oh yeah, and don’t forget to integrate these insights into your career. Follow the implementation steps!
Law 1: Success in Marketing is a Marathon, Not a Sprint
Navigating the tumultuous seas of digital marketing necessitates a steadfast ship, fortified by a strategic long-term vision. It’s a marathon, not a sprint.
Take Apple, for instance. The late ’90s saw them on the brink of bankruptcy. Instead of grasping at quick, temporary fixes, Apple anchored themselves in a long-term vision. A vision that didn’t just stop at survival, but aimed for revolutionary contributions, resulting in groundbreaking products like the iPod, iPhone, and iPad.
In a landscape where immediate gains often allure businesses, it’s essential to remember that these are transient. A focus merely on the immediate returns leaves businesses scurrying on a hamster wheel, chasing after fleeting successes, but never really moving forward.


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A long-term vision, however, acts as the north star, guiding businesses through immediate challenges while ensuring sustainable success and consistent growth over time.
Consider This Analogy:
Building a business is like growing a tree. Initially, it requires nurturing, patience, and consistent care. But with time, the tree grows, becoming strong and robust, offering shade and fruits—transforming the landscape. The same goes for business. A vision, perseverance, and a long-term strategy are the nutrients that allow it to flourish, creating a sustainable presence in the market.
Implementation Steps:
- Begin by planning a content calendar focused on delivering consistent value over the next six months.
- Ensure regular reviews and necessary adjustments to your long-term goals, keeping pace with evolving market trends and demands.
- And don’t forget the foundation—invest in robust systems and ongoing training, laying down strong roots for sustainable success in the ever-changing digital marketing landscape.
Law 2: Survey, Listen, and Serve
Effective marketing hinges on understanding and responding to the customer’s needs and preferences. A robust, customer-centric approach helps in shaping products and services that resonate with the audience, enhancing overall satisfaction and loyalty.
Take Netflix, for instance. Netflix’s evolution from a DVD rental company to a streaming giant is a compelling illustration of a customer-centric approach.
Their transition wasn’t just a technological upgrade; it was a strategic shift informed by attentively listening to customer preferences and viewing habits. Netflix succeeded, while competitors such a Blockbuster haid their blinders on.
Here are some keystone insights when considering how to Survey, Listen, and Serve…
Customer Satisfaction & Loyalty:
Surveying customers is essential for gauging their satisfaction. When customers feel heard and valued, it fosters loyalty, turning one-time buyers into repeat customers. Through customer surveys, businesses can receive direct feedback, helping to identify areas of improvement, enhancing overall customer satisfaction.
Engagement:
Engaging customers through surveys not only garners essential feedback but also makes customers feel valued and involved. It cultivates a relationship where customers feel that their opinions are appreciated and considered, enhancing their connection and engagement with the brand.
Product & Service Enhancement:
Surveys can unveil insightful customer feedback regarding products and services. This information is crucial for making necessary adjustments and innovations, ensuring that offerings remain aligned with customer needs and expectations.
Data Collection:
Surveys are instrumental in collecting demographic information. Understanding the demographic composition of a customer base is crucial for tailoring marketing strategies, ensuring they resonate well with the target audience.
Operational Efficiency:
Customer feedback can also shed light on a company’s operational aspects, such as customer service and website usability. Such insights are invaluable for making necessary enhancements, improving the overall customer experience.
Benchmarking:
Consistent surveying allows for effective benchmarking, enabling businesses to track performance over time, assess the impact of implemented changes, and make data-driven strategic decisions.
Implementation Steps:
- Regularly incorporate customer feedback mechanisms like surveys and direct interactions to remain attuned to customer needs and preferences.
- Continuously refine and adjust offerings based on customer feedback, ensuring products and services evolve in alignment with customer expectations.
- In conclusion, adopting a customer-centric approach, symbolized by surveying, listening, and serving, is indispensable for nurturing customer relationships, driving loyalty, and ensuring sustained business success.
Law 3: Build Trust in Every Interaction
In a world cluttered with countless competitors vying for your prospects attention, standing out is about more than just having a great product or service. It’s about connecting authentically, building relationships rooted in trust and understanding. It’s this foundational trust that transforms casual customers into loyal advocates, ensuring that your business isn’t just seen, but it truly resonates and remains memorable.


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For instance, let’s talk about Oprah! Through vulnerability and honest connections, Oprah Winfrey didn’t just build an audience; she cultivated a community. Sharing, listening, and interacting genuinely, she created a media landscape where trust and respect flourished. Oprah was known to make her audience and even guests cry for the first time live. She had a natural ability to build instant trust.
Here are some keystone insights when considering how to develop and maintain trust…
The Unseen Fast-Track
Trust is an unseen accelerator. It simplifies decisions, clears doubts, and fast-forwards the customer journey, turning curiosity into conviction and interest into investment.
The Emotional Guardrail
Trust is like a safety net or a warm embrace, making customers feel valued, understood, and cared for. It nurtures a positive environment, encouraging customers to return, not out of necessity, but a genuine affinity towards the brand.
Implementation Steps:
- Real Stories: Share testimonials and experiences, both shiny and shaded, to build credibility and show authenticity.
- Open Conversation: Encourage and welcome customer feedback and discussions, facilitating a two-way conversation that fosters understanding and improvement.
- Community Engagement: Actively participate and engage in community or industry events, align your brand with genuine causes and values, promoting real connections and trust.
Navigating through this law involves cultivating a space where authenticity leads, trust blossoms, and genuine relationships flourish, engraving a memorable brand story in the hearts and minds of the customers.
Guarantee Your Success With These Foundational Laws
Navigating through the world of business is a demanding odyssey that calls for more than just adaptability and innovation—it requires a solid foundation built on timeless principles. In our exploration, we have just unraveled three indispensable laws that stand as pillars supporting the edifice of sustained marketing success, enabling businesses to sail confidently through the ever-shifting seas of the marketplace.
Law 1: “Success in Marketing is a Marathon, Not a Sprint,” advocates for the cultivation of a long-term vision. It is about nurturing a resilient mindset focused on enduring success rather than transient achievements. Like a marathon runner who paces themselves for the long haul, businesses must strategize, persevere, and adapt, ensuring sustained growth and innovation. The embodiment of this law is seen in enterprises like Apple, whose evolutionary journey is a testament to the power of persistent vision and continual reinvention.
Law 2: “Survey, Listen, and Serve,” delineates the roadmap to a business model deeply intertwined with customer insights and responsiveness. This law emphasizes the essence of customer-centricity, urging businesses to align their strategies and offerings with the preferences and expectations of their audiences. It’s a call to attentively listen, actively engage, and meticulously tailor offerings to resonate with customer needs, forging paths to enhanced satisfaction and loyalty.
Law 3: “Build Trust in Every Interaction,” underscores the significance of building genuine, trust-laden relationships with customers. It champions the cultivation of a brand personality that resonates with authenticity, fostering connections marked by trust and mutual respect. This law navigates businesses towards establishing themselves as reliable entities that customers can resonate with, rely on, and return to, enriching the customer journey with consistency and sincerity.
These pivotal laws form the cornerstone upon which businesses can build strategies that withstand the tests of market volatility, competition, and evolution. They stand as unwavering beacons guiding enterprises towards avenues marked by not just profitability, but also a legacy of value, integrity, and impactful contributions to the marketplace. Armed with these foundational laws, businesses are empowered to navigate the multifaceted realms of the business landscape with confidence, clarity, and a strategic vision poised for lasting success and remarkable achievements.
Oh yeah! And do you know Newton’s Law?The law of inertia, also known as Newton’s first law of motion, states that an object at rest will stay at rest, and an object in motion will stay in motion… The choice is yours. Take action and integrate these laws. Get in motion!
MARKETING
Intro to Amazon Non-endemic Advertising: Benefits & Examples

Amazon has rewritten the rules of advertising with its move into non-endemic retail media advertising. Advertising on Amazon has traditionally focused on brands and products directly sold on the platform. However, a new trend is emerging – the rise of non-endemic advertising on this booming marketplace. In this article, we’ll dive into the concept of non-endemic ads, their significance, and the benefits they offer to advertisers. This strategic shift is opening the floodgates for advertisers in previously overlooked industries.
While endemic brands are those with direct competitors on the platform, non-endemic advertisers bring a diverse range of services to Amazon’s vast audience. The move toward non-endemic advertising signifies Amazon’s intention to leverage its extensive data and audience segments to benefit a broader spectrum of advertisers.
Endemic vs. Non-Endemic Advertising
Let’s start by breaking down the major differences between endemic advertising and non-endemic advertising…
Endemic Advertising
Endemic advertising revolves around promoting products available on the Amazon platform. With this type of promotion, advertisers use retail media data to promote products that are sold at the retailer.
Non-Endemic Advertising
In contrast, non-endemic advertising ventures beyond the confines of products sold on Amazon. It encompasses industries such as insurance, finance, and services like lawn care. If a brand is offering a product or service that doesn’t fit under one of the categories that Amazon sells, it’s considered non-endemic. Advertisers selling products and services outside of Amazon and linking directly to their own site are utilizing Amazon’s DSP and their data/audience segments to target new and relevant customers.
7 Benefits of Running Non-Endemic Ad Campaigns
Running non-endemic ad campaigns on Amazon provides a wide variety of benefits like:
Access to Amazon’s Proprietary Data: Harnessing Amazon’s robust first-party data provides advertisers with valuable insights into consumer behavior and purchasing patterns. This data-driven approach enables more targeted and effective campaigns.
Increased Brand Awareness and Revenue Streams: Non-endemic advertising allows brands to extend their reach beyond their typical audience. By leveraging Amazon’s platform and data, advertisers can build brand awareness among users who may not have been exposed to their products or services otherwise. For non-endemic brands that meet specific criteria, there’s an opportunity to serve ads directly on the Amazon platform. This can lead to exposure to the millions of users shopping on Amazon daily, potentially opening up new revenue streams for these brands.
No Minimum Spend for Non-DSP Campaigns: Non-endemic advertisers can kickstart their advertising journey on Amazon without the burden of a minimum spend requirement, ensuring accessibility for a diverse range of brands.
Amazon DSP Capabilities: Leveraging the Amazon DSP (Demand-Side Platform) enhances campaign capabilities. It enables programmatic media buys, advanced audience targeting, and access to a variety of ad formats.
Connect with Primed-to-Purchase Customers: Amazon’s extensive customer base offers a unique opportunity for non-endemic advertisers to connect with customers actively seeking relevant products or services.
Enhanced Targeting and Audience Segmentation: Utilizing Amazon’s vast dataset, advertisers can create highly specific audience segments. This enhanced targeting helps advertisers reach relevant customers, resulting in increased website traffic, lead generation, and improved conversion rates.
Brand Defense – By utilizing these data segments and inventory, some brands are able to bid for placements where their possible competitors would otherwise be. This also gives brands a chance to be present when competitor brands may be on the same page helping conquest for competitors’ customers.
How to Start Running Non-Endemic Ads on Amazon
Ready to start running non-endemic ads on Amazon? Start with these essential steps:
Familiarize Yourself with Amazon Ads and DSP: Understand the capabilities of Amazon Ads and DSP, exploring their benefits and limitations to make informed decisions.
Look Into Amazon Performance Plus: Amazon Performance Plus is the ability to model your audiences based on user behavior from the Amazon Ad Tag. The process will then find lookalike amazon shoppers with a higher propensity for conversion.
“Amazon Performance Plus has the ability to be Amazon’s top performing ad product. With the machine learning behind the audience cohorts we are seeing incremental audiences converting on D2C websites and beating CPA goals by as much as 50%.”
– Robert Avellino, VP of Retail Media Partnerships at Tinuiti
Understand Targeting Capabilities: Gain insights into the various targeting options available for Amazon ads, including behavioral, contextual, and demographic targeting.
Command Amazon’s Data: Utilize granular data to test and learn from campaign outcomes, optimizing strategies based on real-time insights for maximum effectiveness.
Work with an Agency: For those new to non-endemic advertising on Amazon, it’s essential to define clear goals and identify target audiences. Working with an agency can provide valuable guidance in navigating the nuances of non-endemic advertising. Understanding both the audience to be reached and the core audience for the brand sets the stage for a successful non-endemic advertising campaign.
Conclusion
Amazon’s venture into non-endemic advertising reshapes the advertising landscape, providing new opportunities for brands beyond the traditional ecommerce sphere. The blend of non-endemic campaigns with Amazon’s extensive audience and data creates a cohesive option for advertisers seeking to diversify strategies and explore new revenue streams. As this trend evolves, staying informed about the latest features and possibilities within Amazon’s non-endemic advertising ecosystem is crucial for brands looking to stay ahead in the dynamic world of digital advertising.
We’ll continue to keep you updated on all things Amazon, but if you’re looking to learn more about advertising on the platform, check out our Amazon Services page or contact us today for more information.
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