Demand generation software has become essential for modern B2B marketing teams, but not all platforms are created equal. VPs of Demand Generation, CMOs, and Marketing Operations leaders must scrutinize potential platforms through a clear checklist of criteria.
From data quality to AI capabilities, today’s demand gen solutions (eg, 6sense, Demandbase, Mutiny, Warmly, and others) promise AI-driven insights and automation—but savvy buyers will evaluate these claims against concrete requirements.
The following sections present six key checklist items to assess before investing in a demand generation platform, each grounded in methodology and supported by industry data.
Finally, we’ll examine how Warmly stacks up against these criteria in practice.
Sources
The statistics in this article are supported by research from Gartner, Forrester, McKinsey, and other industry analysts, as cited throughout, to provide an objective foundation for each checklist recommendation.
Demand Generation Software Checklist
1. Data Quality & Enrichment Capabilities
- Data freshness ✅
- Data validation ✅
- Privacy-first ✅
2. Intent Signal Accuracy and Coverage
- Waterfall approach ✅
- Lead Filtering ✅
- Speed to signal ✅
3. AI and Automation Capabilities
- AI Lead Scoring ✅
- AI personalization ✅
- Routing & Alerting ✅
4. Omnichannel Engagement and Orchestration
- Channels supported ✅
- Orchestration complexity ✅
- Contact data for Person-Based Marketing ✅
5. CRM and Marketing Stack Integration
- CRM custom fields read/write ✅
- Extended channel integration ability ✅
- Export, webhooks & AIs ✅
6. Agentic Future
- Human-in-the-loop ✅
- AI marketing agents ✅
- AI sales agents ✅
1. Data Quality and Enrichment Capabilities
Bad or incomplete data can derail marketing efforts, leading to wasted outreach and missed opportunities. Gartner estimates that poor data quality costs organizations an average of $12.9 million annually. This is unsurprising given how quickly B2B data grows stale—B2B contact data accuracy can erode by up to 70% annually without ongoing updates.
When evaluating demand generation software, buyers should investigate how a platform handles:
Source and Freshness of Data
Does the platform provide data enrichment via reputable providers?
Data Cleansing and Validation
What mechanisms exist to de-duplicate records, correct errors, and fill in missing fields?
Privacy-First Approach to Data
Beyond basic SOC2 compliance, businesses handling data globally should be registered in the US as data brokers and be GDPR compliant. As of publishing, at least five US states have state-specific privacy regulations, and you should ask for a list of all the platform’s sub-processors to ensure compliance.
Resources
How to Evaluate Data Vendors (by Warmly’s in-house data expert)
The leading demand generation platforms differentiate themselves with robust data ecosystems. For instance, some solutions bundle data from multiple sources—in one case, a vendor might offer “all-in-one” access to enrichment and intent data (eg, combining Clearbit, Bombora, etc.) as part of the package. The goal is to ensure your team is acting on high-quality, current data about accounts and prospects.
2. Intent Signal Accuracy and Coverage
Most advanced demand gen platforms tout their ability to identify buying intent, surfacing signals that a prospect is “in market” or showing interest. However, buyers should critically assess how accurate and comprehensive these intent signals are. An intent-driven program is only as good as the relevance of its alerts.
Key considerations include:
Signal Sources
Does the software capture first-party intent (e.g., website page visits, content downloads), second-party intent (e.g., social media site signals), and integrate third-party intent data (industry web research, review sites, Bombora intent topics, etc.)?
Relying on multiple sources can improve accuracy. In fact, over 70% of companies using intent data leverage multiple providers to broaden their coverage, and almost half ingest intent data from three or more sources. A platform that aggregates or waterfalls several intent feeds (for example, combining data from providers like Demandbase, G2, Bombora) will likely paint a fuller picture of prospect interest.
Precision and Filtering
How does the platform determine which intent signals truly indicate a qualified buyer? Top solutions use AI models or rule-based scoring to filter out false positives. For instance, 6sense and Demandbase (leaders in account-based marketing) apply predictive analytics to intent data, helping prioritize accounts with statistically higher conversion propensity. When testing a tool, ask for evidence of its signal precision—case studies or metrics showing improved outbound response rates or sales productivity can indicate reliable intent modeling.
Timeliness and Context
Real-time or near-real-time intent is valuable for acting at the right moment. Check if the platform updates intent insights continuously and provides context (e.g., which topics a target account is researching). Without context, sales teams might struggle to tailor their outreach even if they know an account shows “surging” intent. Note that real-time signals mean within a minute or two, whereas some platforms only update their signals daily, weekly, or monthly.
Resource
Understanding 1st, 2nd & 3rd Party Intent Data (by Warmly’s in-house data expert)
Signal accuracy has a direct impact on pipeline generation. In a Forrester survey, over 85% of companies using intent data reported achieving business benefits such as higher outbound email response rates and more successful sales prospecting.
However, the same research also noted gaps between expectations and outcomes when intent data is not used correctly, indicating that simply having data isn’t enough; it must be accurate and actionable.
Buyers should therefore validate the platform’s intent signals in a pilot or proof-of-concept and favor vendors with transparent methodologies. Said another way: Blackbox intent models used by the same industry leaders (6sense & Demandbase) are outdated in the ABM 2.0 landscape.
3. AI and Automation Capabilities
Nearly every demand generation tool today claims some form of artificial intelligence or automation. The challenge for buyers is to cut through the hype and determine how advanced and useful a platform’s AI capabilities truly are. At a baseline, demand generation software should automate repetitive tasks, but best-in-class platforms use AI to drive smarter decision-making and personalization at scale. Consider the following when evaluating AI and automation:
AI Lead Scoring
Does the AI analyze data to predict which leads or accounts are most likely to convert? Ingesting your CRM data and data about your ICP should allow a good AI Lead Scoring model to predict propensity to buy, allowing marketing and sales to focus on the highest-value targets.
AI Personalization
Some solutions incorporate AI to dynamically personalize outreach—for example, Mutiny’s platform uses AI to tailor website headlines and calls-to-action for each visitor, and other tools use AI to generate email copy or sales scripts. Evaluate whether the AI can actually create or adapt content in a meaningful way (e.g., using large language models for personalization) or if it’s limited to simple rule-based personalization. High-performing marketing organizations are already leveraging generative AI for content; 84% of “high-performing” marketing teams use generative AI in creative work, according to Gartner’s latest CMO survey.
Routing & Alerting
The platform should automate multi-step workflows. This could mean automatically adding a lead to an email nurture, alerting a sales rep on Slack when an account hits an intent threshold, or launching a targeted ad campaign—all without manual intervention. Look into how routing rules work. Can you send leads to reps based on territories (geographic, size-based, industry)? You never know when your RevOps team will redo how territories are done.
Lastly, if the platform aims to help you with inbound lead conversion, ensure that round-robin’ing is built into the platform for the even distribution of leads. Default is a good example of a demand generation tool that does this well.
Resource
How to Use AI in Your Sales and Marketing Tech Stack (by Warmly’s in-house data expert)
Artificial intelligence is now used in virtually every aspect of marketing operations, so look for platforms that weave AI into the core product (not as an afterthought add-on). While evaluating AI features, request demos of specific use cases, e.g., an AI-driven campaign launch or a discussion of how the system adapts over time.
Additionally, ask about the results current customers see—are they actually reducing manual work or increasing conversion rates thanks to AI?
Remember that AI is not a goal in itself; it’s a means to increase efficiency and effectiveness. Adoption is growing fast (only about 10% of marketers now say they have no plans to use AI in their work), so your chosen platform should be keeping pace with this trend. The right solution will augment your team, acting as a “force multiplier” that handles analysis and repetitive tasks so your people can focus on strategy and creativity.
4. Omnichhannel Engagement and Orchestration
Today’s B2B buyers traverse many channels—from search and social media to webinars, review sites, emails, and beyond. To generate demand effectively, your software must enable an omnichannel engagement strategy. This means reaching and nurturing prospects across the channels they frequent, with a consistent message, and coordinating those touches for maximum impact. Key questions to evaluate:
Channels Supported
Identify which channels the platform can manage or integrate with. Common ones include email marketing, digital ads (display, LinkedIn, Google), website personalization, chatbots or live chat on your site, SMS/text, and even direct mail or outbound calling via integrations. A robust demand gen platform will allow multi-channel campaign builds—for example, serving a LinkedIn ad to a target account, then emailing them a whitepaper, and later triggering a sales call task, all as part of one workflow. If a solution only handles one channel (say, just email automation), it may limit your ability to engage buyers who prefer other touchpoints.
Orchestration Logic
Beyond supporting channels, how well does the tool coordinate them? Look for features like journey orchestration or sequencing that adjust the next touch based on buyer behavior. For instance, if a prospect interacts on LinkedIn but not via email, the system might shift budget toward LinkedIn ads for that person. Account-based marketing platforms such as Terminus, Salesloft & Outreach shine here by enabling coordinated, multi-channel sales & marketing campaigns from one interface.
Contact Data for Person-Based Marketing
Most intent data signals (especially from legacy ABM platforms) only generate account-level leads. This is helpful, but you need to reach out to an actual person to build pipeline. Going to the person-level is relatively new but exciting in Demand Gen. Providers like Warmly, RB2B, and Vector are the first in the space to offer person-based marketing. If your signals offer account-level leads, then you’ll need to make sure they provide high-quality contact data to
Clear trends back the importance of omnichannel engagement: 94% of B2B decision makers now view omnichannel as equally or more effective than traditional single-channel sales models. Buyers flip between self-service digital research and human interactions, so your demand generation platform should empower you to be everywhere your buyer is.
For example, some tools integrate a chatbot on your website that ties into email nurture streams, while others can trigger LinkedIn InMail via automation. The recommended checklist includes verifying integrations or native capabilities for social media (especially LinkedIn for B2B), content syndication, ads, email, events/webinars, and direct sales touches.
5. CRM and Marketing Stack Integration
No demand generation platform exists in isolation. It must fit into your existing sales and marketing tech stack, with CRM integration being especially critical. For most B2B organizations, the CRM (e.g., Salesforce or HubSpot CRM) is the central source of truth for leads, contacts, accounts, and pipeline. If your new software doesn’t seamlessly integrate with CRM and other key systems, you risk data silos and process breakdowns.
As you evaluate options, make sure to check:
CRM integration depth & custom fields
Does the platform offer a native, real-time integration with your CRM? Essential capabilities include syncing leads/contacts and their activities, updating account or opportunity fields (such as intent scores or campaign responses), and creating tasks or alerts for sales reps. Ask for any history of downtime or overwriting data—these would have catastrophic effects on your GTM system. Good demand generation software errs on the side of writing new fields to CRM but not overwriting any data.
Lastly, you will want to use custom fields to be able to sync in additional signals or lead scoring logic. For example, a common need is to route based on BDR owner vs Account owner (AE). Account owner is the default field, whereas your sales operations team might have an additional custom field called BDR owner. You’ll need to be able to utilize this throughout a good demand generation platform.
Extended channel integration ability
Beyond CRM, consider other systems like your marketing automation platforms (Marketo, HubSpot Marketing, Pardot, Drift, Qualified, etc.), email systems, webinar software, and sales engagement tools (Outreach, Salesloft). Good demand generation software could either replace some of these or connect to them. For example, Warmly has built a native AI chatbot to replace legacy chatbots like Drift. However, it does not have a native email sequencer and is instead integrated with Outreach & Salesloft.
Export, webhooks & APIs
Even if native integrations are limited, does the platform allow flexible data export, webhooks, or open APIs? This will determine if your engineering team can connect it to your data warehouse or custom workflows, or middleware providers like Clay.
Look for customer references or demos illustrating data flowing from the platform into Salesforce or HubSpot in real time, and read help-center documentation. Finally, consider the vendor’s partnership ecosystem: a strong ecosystem is a sign that integration has been proven out by many other customers. In short, verify that the “plumbing” works—it may not be the flashiest checklist item, but it’s arguably one of the most important to get right for long-term success.
6. Agentic Future
The next evolution of demand generation is driven by AI-powered agents—tools that automate, personalize, and optimize marketing and sales activities without human bottlenecks. This shift enables leaner, smarter teams to produce greater results.
Forrester found that companies using AI-powered sales and marketing automation tools saw 1.5x faster pipeline velocity.
And at the same time that agentic future (as of 2025) isn’t quite “here” yet, there is still great value in demand generation marketers utilizing human SDRs to do work.
What are AI Marketing & Sales Agents?
AI Marketing Agents and AI Sales Agents work together to:
- Continuously monitor buyer intent signals
- Dynamically generate person-level campaigns
- Automate multi-channel outreach (email, LinkedIn, chat, calls, ads)
- Trigger human involvement only at key inflection points
AI GTM agents can and will provide huge boosts to marketers:
- Creating dynamic TAM with AI Marketing Ops Agents (traditional firmographics miss up to 50% of potential market due to outdated filters)
- Reducing conversion leakage from inbound forms with AI-powered chatbots and timely pop-ups with AI Demand Gen Agents.
- Running omnichannel outbound campaigns that A/B test & update on learnings with AI Demand Gen Agents.
- Saving money on agencies & SDRs, but instead using much more cost-effective AI SDR agents.
- Accelerate the future where marketers will own all of pipeline generation (managing SDRs and owning full-funnel acquisition)
So when evaluating a Demand Generation Platform, look into:
Human-in-the-loop
How does the system alert humans to leads and notify humans of errors? Where can humans put in input, and how can you segment humans to work on the hottest and most enterprise-y leads?
Does your human team enjoy using the platform or believe it will save them time/effort? Are there AI co-pilot features that assist your human team?
AI marketing agents
Which parts of your marketing GTM system can you add marketing agents to? Is there agentic data collection? Lead scoring? Orchestration? If not, will this be on their roadmap in the coming year or two?
AI sales agents
Which parts of your sales GTM system can you add sales agents to? Is there an agentic inbound follow-up? Content personalization? Account prospecting? Outbound emailing or LinkedIn DM’ing? If not, will this be on their roadmap in the next year or two?
How Does Warmly Stack Up to This?
Having outlined the core checklist for evaluating demand generation software, let’s assess Warmly against these criteria. Warmly position ourselves as an agentic demand generation platform, and we compete broadly in the account-based marketing and sales space.
Here’s how Warmly measures up on each checklist item:
| Checklist Headline | Checklist Specific | Supported |
|---|
| Data Quality & Enrichment Capabilities | Data freshness | ✅ |
| Data Quality & Enrichment Capabilities | Data validation | ✅ |
| Data Quality & Enrichment Capabilities | Privacy-first | ✅ |
| Intent Signal Accuracy and Coverage | Waterfalled approach | ✅ |
| Intent Signal Accuracy and Coverage | Lead filtering | ✅ |
| Intent Signal Accuracy and Coverage | Speed to signal | ✅ |
| AI and Automation Capabilities | AI Lead Scoring | ✅ |
| AI and Automation Capabilities | AI Personalization | 🟨 (Q3 2025) |
| AI and Automation Capabilities | Routing & Alerting | ✅ |
| Omnichannel Engagement and Orchestration | Channels supported | ✅ |
| Omnichannel Engagement and Orchestration | Orchestration complexity | ✅ |
| Omnichannel Engagement and Orchestration | Contact data for Person-Based Marketing | ✅ |
| CRM and Marketing Stack Integration | CRM custom fields read/write | ✅ |
| CRM and Marketing Stack Integration | Extended channel integration ability | ✅ |
| CRM and Marketing Stack Integration | Export, webhooks & AIs | ✅ |
| Agentic Future | Human-in-the-loop | ✅ |
| Agentic Future | AI marketing agents | ✅ |
| Agentic Future | AI sales agents | 🟨 Yes, via partnership |
In summary, Warmly aligns very well with the buyer’s checklist we outlined. We offer high data quality by aggregating top data sources, accurate intent signals through multi-source monitoring, sophisticated AI automation that acts on insights instantly, authentic omnichannel engagement (spanning email, ads, chat, and social), and seamless CRM integration to close the loop.
Our unique differentiator is combining all these strengths in an autonomous, AI-driven system tailored for smaller marketing teams. While many platforms might meet one or two of the checklist items, Warmly aims to check all the boxes in one solution.
If you’re a VP of Demand Generation or CMO evaluating your options, Warmly is worth comparing against well-known players like 6sense or Demandbase—especially if you seek a vendor-neutral, all-in-one platform that can rapidly turn intent signals into revenue without a large operations staff.
The checklist above can serve as your guide in that evaluation, ensuring whichever software you choose will empower your marketing efforts in a data-driven, efficient, and scalable way.