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17 | 03 | 2025

How to choose your next martech solution wisely

Choosing a martech tool is a strategic decision for any team, as it impacts productivity, process automation, and business scalability. However, the selection process is not straightforward. In this article, we explore key considerations before acquiring a marketing technology solution, current purchasing trends, and best practices to ensure an effective choice. Considerations for choosing a martech 1. Define needs and objectives Before making a decision, companies should evaluate multiple factors to ensure the solution fits their needs and objectives. The first step in choosing a marketing platform is to be clear about the problems they want to solve. According to Gartner, 54% of marketing teams seek to improve operational efficiency and 44% consider reducing costs. Therefore, it's important to understand how this purchase aligns with a long-term strategy. 2. Understand the category that defines the platform If all marketing platforms say the same thing, it's necessary to consider the category. Given the high degree of specialization among platforms, being an agency, adtech, or martech doesn't mean the same thing. For example, although we can all provide a solution for "media optimization," talking about media auditing isn't the same as talking about media management: while the former refers to a Data Analysis category, the latter refers to an agency or adtech category. 3. Evaluate the reputation of the technology Customer reviews and ratings are a decisive factor when purchasing software. Evaluating awards, recognition, and badges is essential to understand whether a technology is keeping pace with the industry it operates in. According to Gartner, four in ten buyers rely on user reviews before making a decision. In this regard, Bunker DB is positioned as the only Latin American martech recognized by Software Advice in the data analysis category. 4. Prioritize ease of implementation A marketing platform may seem ideal in terms of functionality. However, its ease of implementation will dictate its adoption. What good is having the best solution on the market if it's so complex that we barely get any use out of it? Would you prefer to use 10% of a complex solution or 100% of a simpler one? At this point, it's important to evaluate the estimated implementation time and the estimated learning curve. 5. Prioritize integration capacity Likewise, becoming independent of an IT team requires simple and high-quality integration with other platforms. For example, if the data structure is stored in AWS, Google Cloud, or Microsoft Azure, having that export is essential. If my most used platforms in marketing are Google Ads, Facebook Ads, and TikTok Ads, those integrations will also be required. At this point, it's important to evaluate integration with native connectors. 6. Look for onboarding and technical support Understanding the quality of technical support is also essential. Will it be self-managed, or will there be professionals available to assist me? Will it be in my local language, or are there language limitations I should consider? How many professionals and teams does the platform provide for successful onboarding? A faster onboarding process will allow for a more immediate time-to-value for that solution. 7. Cost as a decisive factor The price of a platform isn't the only cost to consider. When calculating the total cost, you should consider subscription or license costs, one-time implementation and configuration costs, and the human costs of training, technical support, and consulting. For example, does the platform charge per user per month? Does the platform offer discounts for multiple brands or for purchasing a solution package? Why is there hesitation when choosing a martech? Currently, it is estimated that more than 14,000 companies make up the martech ecosystem. Unlike a decade ago, the problem today is not a lack of options, but an overabundance of offerings. With so many alternatives, choosing the right martech has become a challenge for brand managers and growth marketing teams. Among the main difficulties in effectively filtering a handful of relevant options, we find the following: Lack of relevant content. Increasingly, all companies say the same thing or something similar, making it difficult to conduct an in-depth evaluation. All companies may promise to "maximize ROI," "optimize time," or "automate processes," but there are significant differences in how each does it. Without reliable and detailed content, it is difficult to know who to trust. More stakeholders involved. The technology selection process involves more teams within a company. The teams evaluating marketing technology include IT, Marketing, Operations, and Sales, each with their own timeframes and demands. This adds complexity and lengthens decision-making times. Perceived risk and shorter contracts. The cost of a martech leads companies to prefer shorter contracts to reduce risk in case the project doesn't perform as expected. It's very common today to find annual contracts with termination clauses of six months or less. Trends in martech purchasing As if that weren't enough, the martech ecosystem is changing, and certain trends are consolidating when evaluating technology selection. Among them, we identify: Less dependence on IT teams. Given the multiplicity of stakeholders in this decision-making process, there is an explicit focus on mitigating IT department decision-making times, prioritizing business teams to have greater influence in decision-making. In fact, today, 60% of marketing technology buyers are marketing, sales, and operations leaders. This reinforces a trend toward more accessible solutions and user-friendly interfaces. A gap in marketing performance maturity. According to a study by McKinsey, 41% of marketing leaders surveyed consider their marketing performance measurement method to be mature, and only 30% acknowledge that they dynamically adjust their investment. Purchases based on real-life demonstrations or tests. Buyers are no longer satisfied with sales presentations. 40% of buyers seek personalized demonstrations before purchasing. Increasing prioritization of AI. Artificial intelligence tools are helping companies analyze performance data and compare solutions more objectively. 35% of buyers use AI to compare prices. slice1 Final recommendations for choosing the best solution The process of purchasing a martech platform has evolved, and companies must adapt to new strategies to make more informed decisions. Define goals and needs from the start. Prioritize highly rated solutions on comparison platforms. Consider solutions with a good reputation among their customers. Evaluate compatibility and integration with your current tools. Take advantage of trends like AI, live demos, and personalized recommendations. Evaluate ease of implementation. Evaluate the quality of onboarding and the customer support team. Consider the total cost, not just the initial price. Making the right decision can accelerate your company's growth and improve operational efficiency. Make sure you choose wisely!

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28 | 04 | 2025

AI 101: ChatGPT, Copilot y Gemini. Which one is better for marketers?

Artificial Intelligence (AI) is one of the most revolutionary technologies of our time. In 2022, OpenAI launched ChatGPT. Just four days later, this chatbot specialized in natural language had surpassed one million users, and in just one month, it had reached over 265 million users. This was a turning point that pushed all major tech companies to develop their own versions of AI. Today, AI is a key tool for growth, innovation, and competition. From improving business efficiency to enhancing creativity and scientific research, AI is transforming the way we interact with the world. However, many marketing professionals are still unsure about which AI tool is best suited for the specific needs of marketing and data analysis. That’s why, in this article, we invite you to explore a comparison between Copilot, Gemini, and ChatGPT, evaluated across six key categories: integrations, pricing, response quality, performance and speed, data analysis, and predictive analysis and actionable insights. 1. Integration with Professional Tools 🏆 Best Option: Microsoft 365 Copilot. Copilot offers the most seamless integration, ideal for Microsoft-based environments; Gemini works well for organizations operating within Google Workspace; and ChatGPT is technically versatile but requires custom adaptations for integration. Copilot leads in professional integration by working natively within Word, Excel, Outlook, Teams, and Dynamics 365. For example, Copilot can draft an email in Outlook, summarize a meeting in Teams, generate a report in Word using Excel data, or suggest content recommendations for Dynamics 365 clients—all from within the same interface. This allows users to leverage AI directly within their usual workflows without switching platforms, making it especially valuable for corporate marketing teams. Google Gemini also offers strong integration, but it is limited to its own ecosystem: Gmail, Docs, Sheets, Meet, and other Google Workspace products. It stands out for organizations that already use these services and provides connections with data and marketing tools such as Google Analytics and Google Ads. ChatGPT, on the other hand, is not natively integrated into any productivity suite. It operates as an independent application but can be connected via APIs and plugins, offering flexibility but requiring additional development or configuration efforts. 2. Pricing for Professional or Enterprise Use 🏆 Best Option: Google Gemini. Gemini wins in cost-effectiveness for companies already using Google Workspace; Copilot is more expensive but deeply integrated; and ChatGPT offers flexible pricing depending on team size and usage needs. Google Gemini stands out by including AI features at no additional cost in its enterprise Google Workspace plans. This makes Gemini the most accessible option, as it doesn’t require extra per-user fees to use AI in Gmail, Docs, or other apps—an important advantage for larger teams. Copilot, on the other hand, comes with a premium price on top of the standard Microsoft 365 license. This additional cost can be significant for businesses, leading many to carefully assess the ROI before adopting it at scale. ChatGPT offers plans such as Plus, Team, and Enterprise, with pricing that varies based on the user type and usage level. It also provides access via API with a pay-per-token model, which can be either cost-effective or expensive depending on usage intensity. 3. Content Quality, Creativity, and Strategic Thinking 🏆 Best Option: OpenAI ChatGPT. ChatGPT excels in creativity and content strategy; Copilot is strong in enterprise environments with internal data; and Gemini adds value when up-to-date information and SEO optimization are needed. ChatGPT stands out in marketing for its creative capabilities and natural fluency. It generates original, persuasive, and human-sounding text that adapts to brand voice, making it ideal for copywriting, campaign ideas, and strategic planning. It also handles Spanish and cultural nuances very well, producing content that feels emotionally connected and authentic. Copilot delivers similar quality since it uses the same underlying technology, but it shines in enterprise environments with access to internal data. Its focus is more on productivity and personalization within the Microsoft ecosystem. It’s excellent for generating content based on internal documents but tends to be more conservative in terms of creative exploration. Gemini, meanwhile, has significantly improved. Its main strength lies in its web connectivity, enabling it to deliver answers with up-to-date information—great for trend analysis and competitive benchmarking. While it’s less imaginative than ChatGPT, it performs well in SEO-related tasks and producing search-optimized content. 4. Overall Performance and Response Speed 🏆 Best Option: OpenAI ChatGPT. ChatGPT is the fastest and most consistent; Copilot comes close within Office environments; Gemini is competitive but slightly slower when prioritizing real-time information. ChatGPT stands out for its speed and consistency. It responds almost instantly and typically completes answers in just a few seconds, outperforming Gemini in overall responsiveness. This is largely because it generates replies directly from its trained model without needing to search the internet. Infrastructure improvements have also reduced errors and wait times significantly. Copilot, powered by GPT-4 via Azure, offers similar response times within Microsoft 365 apps. It may take slightly longer when analyzing documents or contextual data, but it remains fast and reliable for corporate tasks. Google Gemini is also fast, but often slightly slower than ChatGPT. This is because it frequently pulls real-time data before responding—a valuable feature, though it adds a bit of latency. 5. Data Analysis Capabilities 🏆 Best Option: OpenAI ChatGPT. ChatGPT is the most versatile for exploratory and in-depth analysis; Copilot is practical for operational analysis within Microsoft tools; and Gemini excels in insight accessibility within the Google ecosystem. ChatGPT leads in data analysis thanks to tools like Code Interpreter, which allows it to perform calculations, identify patterns, segment data, and generate visualizations from structured files (CSV, Excel) or unstructured text. It acts as a virtual analyst, combining numerical processing with detailed explanations—all in Spanish and without requiring external programming. Copilot provides effective analysis within Excel and Power BI. It can suggest formulas, detect errors, and answer natural language questions about dashboards. It’s ideal for descriptive analysis within the Microsoft ecosystem, but it doesn’t support advanced coding or custom statistical models. Google Gemini, on the other hand, integrates with Sheets, BigQuery, and Data Studio. It can generate formulas, SQL queries, or data summaries, making insights more accessible—especially in Google Cloud environments. For unstructured text, it performs well using NotebookLM, although it doesn’t reach the analytical depth or flexibility that ChatGPT offers. 6. Predictive Analysis and Actionable Insights 🏆 Best Option: Microsoft 365 Copilot. Copilot is superior for operational predictions and automated actions; ChatGPT provides personalized, on-demand analysis; and Gemini adds value by complementing insights with broader market context. Copilot leads in predictive analytics thanks to its integration with Dynamics 365. It delivers automated lead scoring, sales forecasts, and strategic recommendations directly within CRM and ERP systems, with no manual input required. This gives marketing and sales teams a clear advantage in making data-driven decisions based on historical patterns. ChatGPT allows for predictive analysis on demand if datasets are provided and the advanced analysis feature is enabled. While it doesn't generate forecasts automatically, it’s effective for qualitative strategic suggestions—though it requires user interaction and doesn’t access internal data unless explicitly supplied. Google Gemini doesn’t offer native prediction capabilities, but it can deliver insights when connected to tools like GA4 or Vertex AI. Its access to market data and search trends helps enrich strategy with external benchmarks and up-to-date context. Executive summary Conclusion Comparing AI tools like Copilot, ChatGPT, and Gemini means recognizing that there is no absolute “best.” Each one serves different needs, usage contexts, and levels of specialization. While ChatGPT excels in content generation and advanced conversation, Copilot and Gemini shine in how they connect with their respective professional suites—Microsoft Office and Google Workspace. Choosing one over another depends more on your business objectives and existing tech stack than on a simple ranking. The future of AI is evolving along two simultaneous paths: generalization and specialization. On one hand, large language models are becoming increasingly accessible, integrating into a wide range of products. On the other hand, a wave of specialized solutions—such as ADA AI (by Bunker DB), Jasper, and Copy.ai—is emerging, designed to master specific tasks in niches like marketing, sales, or customer support. The real competitive advantage will come from knowing when to use a general-purpose AI, and when to opt for a specialized tool that truly understands the language, metrics, and nuances of your industry. References Forrester (2025). Google Pressures Microsoft 365 By Adding Gemini To Workspace For (Mostly) Free Highline College (2024). Guide to Microsoft 365 CoPilot and Google Gemini » Information Technology Services Designity (2023). Google Gemini vs. ChatGPT: Which AI Tool is Better for Marketers? - Designity Matter Communications (2024). ChatGPT vs. Google Gemini: Which is Better for PR and Marketing? Pluralsight (2023). ChatGPT Advanced Data Analysis (Code Interpreter): Practical Guide AboutTMC (2023). 7 Benefits and Features of Copilot in Dynamics 365 Sales (CRM) TechTarget (2024). Gemini vs. ChatGPT: What's the difference? | Informa TechTarget TechCrunch (2025). How much does ChatGPT cost? Everything you need to know about OpenAI's pricing plans Medium (2023). Exploring AI for Marketing: Google Gemini vs. ChatGPT | by Le-an Lai Lacaba