Powerful Martech Platforms Tools for B2B Revenue Teams – And How AI Is Boosting Them

Joanna Szumowska

Joanna Szumowska

Focus on the target, not the tool 

You already know it: right now, AI can answer almost all of your digital needs. 


On the Futuropedia website, you can already find over 5,000 tools powered by AI in 54 different categories, and this number is constantly growing. 


Which AI tools to choose? What ROI can you expect? How to use AI martech tools for B2B growth? 


These questions are surely circulating in your organization. And operating in such chaos requires extraordinary caution. 


We should not mindlessly admire AI – it is not important whether the tool is based on AI, but how it responds to the needs of the organization. The long-term perspective is key – how the tool enables the integration of teams around a common goal, which is generating revenue. 


And that’s exactly why I do not want to create another list of such tools, but to propose a slightly broader perspective. I will briefly outline how large martech platforms can improve cooperation between sales, marketing, product management and customer service in the spirit of revenue driven marketing: Revenue Marketing: How to Build Team Alignment Around Generating Income in B2B?


At the end, I will also offer some tips on how to approach choosing the GTM/ABM platform for your organisation. 


Let’s dive in. 


Areas in revenue marketing that can be automated and improved 

Revenue driven marketing is about building a mindset that focuses team activities on generating revenue through cooperation, knowledge flow and process alignment. This enables implementing sustainable activities at the junction of marketing, sales and customer service: 


  • research, analysis, measurement, inference (regarding the market, trends, target groups, leads, clients) 
  • construction of the ICP, identification of the buying committee and its members, segmentation 
  • building brand awareness 
  • demand generation thanks to the production and distribution of valuable content 
  • building a verified CRM database 
  • lead and customer service 
  • buyer intention detection 
  • capturing accounts ready for talks and negotiations 
  • thanks to analysis and prediction – personalized communication and closing sales  
  • quality customer service and retention support. 

 I will briefly discuss several tools that integrate a number of functionalities that enable the implementation of these tasks.  I will also check what role AI plays in their optimization. 


Examples of comprehensive martech platforms designed to generate revenue 

What do the software I mentioned have in common? 


Its purpose is basically to connect the dots – to detect dependencies which are invisible at first glance and traces left by users during their decision-making path, and to skilfully use the data collected by the organization and acquired through listening. 


I understand it as coordinated planning and implementation of tailored, integrated and personalized, and therefore effective, campaigns. 


I took a brief look at several tools that define themselves as GTM, ABM, sales intelligence, sales enablement and revenue intelligence platforms, such as: 


What they have in common is understanding how the decision-making path in B2B is shaped today – it is multi-threaded, tangled, and non-linear. 


These platforms, as indicated by the creators of 6sense, largely focus on answering to Dark Funnel, understood as


ghostly data-realm packed with buyer intent information that revenue teams historically haven’t been able to access.



Tools integrated within the platforms enable you to detect: 

  • Behavioral signals – related to interest in the topic  
  • Buyer readiness signals – related to technology, market information or the current situation of the organization 
  • Buyer psychographic signals – related to the specific characteristics of the members of the buying committee, their interests or the way they communicate. 


So what solutions are available within the platforms, which are attractive not only for marketing and sales, but also for founders, due diligence or HR? 

  • profiling tools: creating profiles of ideal clients and buying committees by searching giant databases of companies and contacts, and linking this data with intelligent recommendations (HR can also look for candidates in these databases) 
  • creating enriched, verified contact cards: lead enrichment and scoring based on a range of market, behavioral or psychographic data (such as website visits, searching for similar solutions or insights from calls or emails) 
  • conversational intelligence – chatbots integrated with databases and alerts enabling lead qualification, insights from conversation transcripts and meeting planning 
  • creating automated campaigns, workflows and salesplays, managing personalized communication with users from one place 
  • customer segmentation, creating tailored messages and personalized outreach: automation of multi-channel contacts with the user 
  • cleaning and unifying data and tasks automation 
  • tracking abandoned forms, obtaining data from them, eliminating redundant addresses and merging data with data in databases 
  • integrations with CRM and techstack, enabling real-time information updating 
  • personalization of websites and real-time CTA based on user information 
  • extending the functionality with browser plugins, optimizing everyday work with contacts 


How does AI enrich these solutions? How can we apply AI in sales and marketing? 

AI allows you to react faster and act smarter and more efficiently. The use of AI focuses on obtaining a 360 view and increasing the efficiency of activities, e.g: 


  • AI analyzes data from dozens of sources: marketing automation, CRM, e-mailings, calendars, social media and other martech platforms. It combines data, cleans it of digital garbage, enriches it with valuable information and creates predictive models. Importantly, it allows you to combine both public and non-public data for the usual analytics of shopping signals. It also allows you to combine lead data with specific accounts and better map the buyer’s journey. You can find more information on this subject on the DemandBase 
  • AI automates ICP creation – more on Zoominfo. 
  • AI supports more effective writing of personalized and data-driven sales texts and cold outreach emails. More on the Seamless or 6sense websites. 
  • AI acts as a co-pilot for more precise actions and says goodbye to spray-and-pray techniques. Provides customized action and lead recommendations based on company and industry data and historical win/lose data. It helps prioritize, track trends, and catch insights based on interactions with leads. More on the Gong website, these solutions are also introduced, for example, by Apollo. 
  • AI enables pipeline analysis and accurate pipeline forecasting. More on the 6sense website. 


These examples show how AI can be used as part of comprehensive martech platforms. In their case, we can see that the use of AI supports the implementation of the broader goals of the organization and is built into the value proposition of the platform. 


How to choose the right martech platforms for your revenue teams? 

Remember that the choice of the tool should result from and be consistent with the brand strategy. You should analyze your options in the context of many internal and product-related aspects. 


When completing your tech stack, you and your team should follow these steps: 


Target mapping  

  • Revise your objectives related to the revenue goal 
  • Analyze and set common KPIs for teams 
  • Analyze the daily tasks performed by different teams and individuals 
  • Map gaps in tasks that should and shouldn’t be performed, as well as possible delays and shortages due to insufficient resources


Tech stack analysis  

  • Update your knowledge about the tools you have and their use in the organization: check whether these tools are used, how they are used, by whom, for what purposes 
  • Check what tech stack is mandatory, what integrations are necessary – that is, what are the limitations in the organization 
  • Verify if your team’s tools have AI updates and what value AI brings 
  • Map the common goals and needs of teams and individuals using the platform. 


Option analysis 

  • Analyze the competition in terms of prices and opportunities  
  • Research pre-selected new tools and make a list of them. Check out the reviews. Compare the cited pros and cons. 


Cost and budget analysis  

  • Set a budget that you can spend on tools 
  • Check tool costs 
  • Consider eliminating redundant, outdated or cost-ineffective tools 
  • Analyze the potential internal costs of “switching” to new tools (onboarding, training) in the context of time and resource consumption. 


Selection of test tools 

  • Consider costs and make testing decisions 
  • Make an appointment for a demo to talk about the specifics of your organization 
  • Schedule tests and collect feedback from the entire team 



  • Test the tools and make sure that the people involved also give them a try 
  • Make your own assessment after a set time and collect feedback from users


Monitoring and optimization 

  • Summarize the conclusions of the tests 
  • Together with the team, discuss the effects of testing, the pros and cons of the tools 
  • Monitor the effects regularly and keep your eye on it 
  • Make further decisions to continue using or test another tool. 


How not to get infected with “toolosis”? 

It goes without saying that every marketer and organization should have their own tech stack. However, nowadays, we can’t only consider the general tech stack, there’s also AI, which allows both individual users and organizations to gain co-pilots that increase productivity, efficiency and quality of work in many fields. 


Your decision considering martech and the degree of platform use should depend on individual needs and goals, budget, constraints, team composition, processes and required integrations. You should also think about security and sensitivity of data used by the company. 


The hype around AI resulted in the public being delighted with spectacular, highly specialized tools that relieve marketers or salespeople in tedious tasks on a daily basis. 


However, it is easy to lose sight of the long-term perspective, focusing on the tools and their stunning possibilities, and not on the goals. You should avoid using tools recklessly, not to catch the disease that I personally call “toolosis”. You also shouldn’t trust AI uncritically, especially considering the evolution of interfaces. 


Perhaps, as my colleague, Tomek Chojnacki, noticed, the integration of AI will go towards the maximum simplification of the interface into one uber-interface. And the key benefits of the platforms will be focused on guessing the user’s intentions and needs based on previous behavior and searches. This significant facilitation, however, can cause intellectual laziness, resulting in wrong decisions made under pressure of AI. 


In the long-term, platforms that implement various tools to integrate processes and teams, encourage the exchange of knowledge and cooperation are the most interesting and valuable. Examples of such tools have been described above. 


Therefore, it is worth spending more time on the AI strategy – it should be included in the broad action plan and strategy of the organization. 


If you need help with the selection of tools and their tests, you can use the consultations within your organization and do research together. You can also entrust the task to an external team of experts who carry out such tasks on a daily basis, testing tools for various clients and for their own needs. Thanks to this, you can gain an external perspective and insights that you may not discover during your own tests. 


When turning on the tool, do not turn off thinking! 


For more information on mindful approach to AI, check out the article about AI usage in B2B marketing in times of crisis. 

Joanna Szumowska



Head of Strategy with nearly 20 years of experience. Specialized in B2B tech marketing, she also gained experience in digital advertising agencies and B2C marketing. A sociologist by training with a background in UX, analytics, research, brand marketing and inbound marketing, she is an advocate of a t-shape approach to competency profiling. A promoter of demand generation based on delivering real values for audiences.

Head of Strategy with nearly 20 years of experience. Specialized in B2B tech marketing, she also gained experience in digital advertising agencies and B2C marketing. A sociologist by training with a background in UX, analytics, research, brand marketing and inbound marketing, she is an advocate of a t-shape approach to competency profiling. A promoter of demand generation based on delivering real values for audiences.

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