How to Utilize Intent Signals in B2B Marketing

I find that most B2B companies that go after enterprise accounts focus too much of their ABX strategy around data and analytics instead of actual engagement. They buy fancy technology that promises to uncover account-level insights (coupled with contact-level data if they’re a bit more advanced) such as views and website visits, maybe sprinkle some 3rd party intent data from G2 and such, and then spend lots of time and resources on making sense of that data. Most of the time, this data becomes yet another white elephant, and the SDRs and AEs that are meant to act on those signals are overwhelmed and confused as to what a healthy next step should be. This is how most ABX programs die - with a lack of attributed impact and zero buy-in from leadership. And it all started with having overly optimistic expectations from ABX measurement tools, and overlooking the actual engagement strategy. Here’s a refined approach: 1. Invest time in account selection and buying group mapping BEFORE the year/quarter starts, and use the intent signals you have to prioritize the accounts you want to go after. 2. Build your ABX demand generation program around creating 3-4 meaningful touchpoints with each relevant contact on your target buying group. Meaningful = creating awareness for the pain you’re solving and for your brand. Extra points if you can get a case study in front of their eyes featuring a competitor of theirs. 3. Collaborate with SD+Sales teams to define what exactly is the engagement strategy (or reachout, if you will) they should pursue when the right signals come in. Nail specific account strategy, and ensure the value prop is clear, then create email templates as a baseline for personalization, set SLAs and spend time on proper enablement. 4. Launch a small scale pilot (25-50 accounts max) with a handful of reps. Make sure the flow is understood and is effective, scale with your successes, and remember to keep celebrating wins with the SD + Sales teams. Getting their commitment is not about fancy Marketing ROI reports, it’s about highlighting specific winning examples. __ Focus your ABX strategy on the actual account activation and engagement. The tools that help you monitor and track aren’t really “ABX platforms”, and with no proper followup you’ll just overflood your team with heaps of worthless data… #abm #ABXstrategy #b2bmarketing

55% of sales leaders witnessed increased lead conversions with intent data, a stat that marks a new era in the art of sales and marketing. 🔍 A Personal Tale: From Data Jungle to Targeted Strategy 🔍 I once partnered with a client who was overwhelmed by a deluge of intent data from Bombora. Picture navigating a dense jungle without a map. The data was vast but unstructured, not effectively mapped to accounts. I was reminded of Craig Rosenberg's words - "The key on intent is fit comes first." 💡 Turning Complexity into Clarity: The Role of Context Our quest was clear: to cut through this jungle and find a path. We initiated a meticulous cleanup, aligning intent data with specific accounts. Then, we took a pivotal step further by focusing on contextual intent data. 🧭 Unlocking the ‘Why’ Behind the Data Contextual intent data is like a compass in uncharted territory. It goes beyond identifying interested accounts; it's about grasping the reasons behind their interest. This deeper understanding enabled us to tailor our approach, addressing the specific needs and challenges of each account. 🌈 The Outcome: Precision-Driven Sales and Marketing Success The transformation was remarkable. Sales dialogues became more focused and resonant. Marketing campaigns struck a chord, addressing the unique context of each account's journey. 🛤️ A 5-Step Blueprint to Mastering Contextual Intent Data Data Harvesting: Collect intent data with an eye for the underlying context of each interaction. Intelligent Mapping: Align this data with specific accounts, illuminating your path through the data forest. Tailored Tactics: Customize your outreach based on the nuanced context of each segment. Adaptive Campaigns: Launch dynamic, context-sensitive campaigns that connect deeply with each account's narrative. Strategic Refinement: Continuously evolve your strategies, responding to the ever-shifting landscape of intent signals and contexts. 📈 Beyond Just Data Points: Contextual intent data isn't merely a collection of information; it's a storytelling tool. It's about transforming raw data into compelling narratives that not only reveal who is ready to buy but also why they are on this journey, creating more meaningful and effective sales and marketing engagements. Step into the world of contextual intent data and watch your sales and marketing narratives change from abstract data points to stories that connect and convert. #ContextualIntentData #SalesInnovation #MarketingTransformation #DataDrivenDecisions #BusinessGrowth #B2Bmarketing #ABM #accountbasedmarketing #METABRAND #IndustryAtom

If I had to build outbound from scratch for Groove again, here's exactly what I'd do to book 10 extra demos a month from scratch: We get 1 qualified lead for every 24 contacts using social signals. The timing and targeting are everything. The complete strategy: Setup (Foundation) 1. Create Clay template (our’s is free to use, just reach out). 2. ICP Rubric: Paste this into ChatGPT: "I want to complete a business rubric. Ask me all the questions you need to fully complete it. Once I answer, reformat everything into a structured rubric." Answer questions about ideal customer profile, pain points, messaging strategy, and buying triggers. Then say: "Format this into a structured rubric." You'll get: "We target {{type of business}}. Keywords: {{keywords}}. Common pitfalls: {{business types to avoid}}. Fit criteria: {{summary}}." Example: "We target B2B SaaS companies. Keywords: 'SaaS,' 'platform,' 'API,' 'automate,' 'CRM,' 'subscription.' Pitfalls: E-commerce stores, consumer mobile apps." 3. Configure Clay: Add target job titles in company filtering. Paste ICP rubric into qualification prompt. Connect to Instantly or HeyReach. Track Social Intent. 1. Trigify Setup: Choose competitors based on: Do they get consistent LinkedIn engagement? Do they talk about your solution? Pro tip: If competitors aren't active, scrape thought-leaders or use scrape for company followers. 2. Connect: Add competitor profiles to Trigify. Attach Clay webhook. Turn on auto-update. LinkedIn engagers automatically flow into Clay. The Messaging 1. Template: {{firstName}}, poke-the-bear question. We built {{tool name}} to {{solve problem}} using {{unique approach}}. {{Short case study or CTA}} Curious to see how it works? Principle: Polarity. Be clear, specific, and take a stance. 2. Real Examples: Email 1A (no CX tools on BuiltWith): "Hey {{firstName}}, BuiltWith didn't surface a CX-specific tool on your stack - curious where your support docs are housed? We built InstantDocs for teams running lightweight CX setups. It comes at no cost, ready to go + we'll handle setup. Up for a quick look?" Follow-up: One follow-up max, under 100 words. Why This Works: Every great outbound message answers: Why this person? (ICP match + competitor engagement) Why now? (Public action showing interest) Social signals provide both. Clay workflow: Import → Enrich → Filter with AI → Validate → Send. Trigify timing: Track engagement → Time outreach → Strike when problem-aware. The Strategy The list is the strategy. Wrong people = no messaging saves you. Social signals show real, high-intent behavior. Someone just engaged with your competitor. Strike while problem is top of mind. Tools needed: - Clay (list building, enrichment) - Trigify (social monitoring) - Instantly/HeyReach (sending) Result: 1 qualified lead for every 24 contacts. What social signals are you tracking?

Over the last 6 months at Factors.ai, we made much progress on leveraging G2 intent signals more fully in our Sales and Marketing Efforts. Outlining the key playbooks below so it may benefit everyone 1️⃣ Building Top of the Funnel ABM lists of ICP accounts showing G2 Intent: Our workflow here involves scoring G2 provided accounts by combining LinkedIn Activity, Website Activity, and G2 signals to categorize accounts into Brand Aware (high on engagement) and Brand Unaware. Brand Unaware accounts are automatically uploaded to LinkedIn into a Top of the Funnel Campaign. Brand Aware accounts are assigned to SDRs and also added to a Bottom of the Funnel campaign on LinkedIn 2️⃣ Trigger customized Chat popups based on G2 Intent signals: When accounts detected by G2, are later detected on the website we trigger specific chat playbooks with messages such as 'Here is a blog/deck on how Factors.ai compares to some of our competitors' 3️⃣ Re-activation of Closed Lost or Inactive Accounts showing G2 Intent: Over time, accounts that have engaged with us in the past but dropped off have grown into a sizeable list. G2 Intent helps us identify which of these accounts are moving into a buying cycle now. Typically such accounts convert faster as they are aware of our product and brand from past interactions 4️⃣ Competitor Intelligence for Opportunity Accounts to AEs: For all active opportunities, a note in Hubspot is automatically populated with information on specific competitors whose G2 pages have been viewed by that prospect. This helps our AEs be better prepared for each demo/prospect meeting and position Factors appropriately in terms of pricing and features to be highlighted 5️⃣ Churn Risk warnings for existing Customers to AEs / CSMs: Similarly, for existing customers, any signal that they are evaluating competitors is added as a churn signal into Hubspot. A task is created for the respective AE and CSM to 1) reach out to the account and schedule a Business Review meeting and 2) Multi Thread with more stakeholders in the account 6️⃣ Build Google Ads ABM Audiences based on G2 Intent: Users who are identified to be from accounts that have shown G2 Intent are pushed into Google Analytics and then Google Ads as an Audience. These users are generally high intent and are then pushed into two ad workflows 1) Display Ads on YouTube and Google Display Network with high bids and 2) Add this audience into an RLSA campaign targeting a broader set of keywords rather than only high intent keywords as done for normal search campaigns 7️⃣ Trigger custom emails to signup users based on G2 intent: Factors gets roughly 200 self-serve signups a month. For self-serve accounts that also show G2 intent we trigger the following workflows 1) automated email to the users who have signed up on how Factors is differentiated 2) Tasks for inbound SDRs to reach out and connect with multiple stakeholders at the company

I'm jazzed people are moving from ABM to Signal-Based Marketing. ABM was often too abstract, and it's refreshing to see it fade to where it belongs, the BACKGROUND 🤔 Why does Signal-Based Marketing make more sense? It's about listening more than pushing. Forget just tracking website visits or generic intent data like many ABM strategies suggest. If that's all you're getting, it's time to look for something better . Here’s a straightforward, effective approach to Signal-Based Marketing: 1️⃣ The Living List: Start with a dynamic target list that needs regular updates and maintenance 2️⃣ Ideal Contacts: Automate the addition of ideal contacts from various databases to continually refresh your list 3️⃣ Deep Listening: Engage deeply with your target audience. Go beyond basic signals like website visits; aim to monitor at least 50 real-time signals to truly understand and stay ahead 4️⃣ True Execution: Extend beyond simple sales alerts. Automate your outreach across emails, LinkedIn, paid media, events, and direct mail for a truly cohesive strategy 5️⃣ Reporting & Insights: Regularly track and assess the effectiveness of your efforts. Focus on the accounts, contacts, and signals you're leveraging. If this strategy seems simple, that's because effective marketing should be straightforward—but don't be fooled; implementing this isn't easy, especially with many technology vendors still catching up. I'm having weekly conversations about how Signal-Based Marketing is changing marketing and frankly, it's damn about time #SignalBasedMarketing #DigitalMarketing #InnovationInMarketing #ABM #B2BMarketing

More traffic to your website ≠ more leads and revenue. In late 2019, Help Scout hired me to help recover organic traffic they lost after a site migration. They’d implemented redirects for the migration properly — done everything right as far as I could tell — but they were only seeing about 60% of the organic traffic they had pre-migration. I worked for the next year to help them recover the traffic they’d lost. We updated many blog posts, identified and solved technical issues, and added hundreds of internal links. Before the end of 2020, the traffic was not only back to pre-migration levels, it had surpassed it. Big win, right? Wrong. Yes, we were getting more traffic than ever, but that traffic wasn’t converting. More traffic didn’t equate to more leads. More traffic didn’t generate more revenue. Why? People use search engines to find answers to questions. They usually pay zero attention to who provided the answer. They’re getting their answer, leaving, and forgetting you exist. Unless the answer they’re looking for is your product. So in 2021, we pivoted our SEO strategy to focus on purchase intent keywords — search terms that suggested the searcher was actively shopping for a product like ours. That year, we increased first-touch trials from content by 50%. In 2022, they went up another 53%. And not only did we increase trials, but the trial-to-paid conversion rates from our purchase intent content was considerably higher than trials from other channels. In my newsletter this week, I go into detail about how I find purchase intent keywords for B2B software brands. To read it, follow my profile 🔗 👆 and click “Newsletter” in the main nav.

Typically, I see growth teams focusing on the biggest funnel drop, but this is usually not the biggest opportunity for growth, and unproductive. Let me explain by going deeper into a more holistic approach to managing growth funnels. Most of the analytics tools available today offer limited funnel metrics: funnel drops and completions. It’s therefore understandable that teams focus on the biggest drop. The truth is - most users won’t complete your funnel anyway. Your product probably wasn’t built for them, there’s no product-market fit, and changing their low intent is unlikely. Optimizing might keep them 1-2 more stages, but they’ll likely churn at the next. Move on! Your best opportunity lies with high-intent users who don’t complete the funnel. They have a good product-market fit and should complete. First identifying this group is crucial to understanding why some don’t succeed. How to identify High-Intent Users: Try changing up your analytics approach, put the dashboards, #correlation, and lengthy #abtesting aside for a minute. Here are a few ways to help you identify your high-intent users. Search for the signals of intent: Shorter time to complete steps, differences in onboarding questions and responses, permissions etc. Group users into segments, such as the marketing received, localizations, user properties, and behavioral groups. Calculate the likelihood of users in a sub-segment completing the funnel. Then, upon aggregating all the sub-segments together, you understand the quality and intent of the segment. Users with the most signals of intent are your high-intent users. Find high-intent users automatically. Consider leveraging a causal model. Loops, for example, automatically identifies high-intent users, by looking at the sub-segments and finding intent signals. It can otherwise be a very manual process when you are limited to funnel drop and completion metrics. How to Identify the Biggest Opportunities: Once you have identified your high-intent users, you need to size the opportunity before starting to form hypotheses. Opportunity size is based on the questions: Assuming this segment completed this step of the funnel, what would be the effect on the total funnel completion rate. Loops automatically presents you the biggest opportunities to improve your funnel. It calculates what would be the impact on the total funnel completion rate, if you improve a specific step of the funnel. Action the Insight: By identifying high-intent users and their pain points and motivations you can better shape the top of the funnel and increase completions. Armed with the confidence and impact insight of your biggest opportunity, you can turn your attention to the specific actions needed for funnel completion, as expected. Remember, most users will drop. Invest your time in identifying and understanding high-intent users. Causal inference models can help you find the answer, with less time, effort, and stress. #productledgrowth #causalml #growth

Make no mistake—the decline in outbound response rates in 2023 has dealt a heavy blow, forcing sales organizations of every stripe to make difficult pivots. Battling the headwinds of shifting customer preferences and intense scrutiny of B2B investments, sales teams have responded by honing their ideal customer profiles and buying committee personas with surgical precision to the new market realities. From there, organizations are taking two approaches: 1️⃣ Leverage AI and automation to scale inside sales activities and offset lower engagement rates. • In most cases, it comes in the form of sellers using AI assistants or copilots to help them. In 2023, some providers pushed the envelope by building solutions to automate the entire sales process —from research to outreach and warm-up. • These take different forms under names like AI S/BDRs, digital sales, conversational email, and more. • Examples include AISDR and Sailes for outbound prospecting and Conversica or Saleswhale, a 6sense company for inbound lead engagement. 2️⃣ Use buying signals and intent data to identify the best prospects to go after right now. • AI is enabling new approaches to combine intent data (content consumed or ads served/clicked) with a broader set of signals such as employees switching companies, new purchases, job descriptions, or website visits. • It is paving the way for a new breed of platforms that aggregate these signals, use AI to make sense of them and score the best accounts to go after. • Some vendors even add demographic, firmographic, and technographic data either from sales intelligence providers or by scouting the internet. • Examples include Common Room, Lead Onion, or MadKudu. I am thinking of adding these two categories to my SalesTech landscape. So, I’m eager to learn what approaches and enabling technologies you see gaining adoption despite the outbound challenge. Please share your perspectives and experiences in the comments below. #outbound #intent #automation #salestech

If I were a growth marketer stepping into a new B2B SaaS role, these are the first 2 signal-based campaigns I’d run. ⤵ → Past opportunity expressed interest in X feature that now maps to an upcoming product release → Past opportunity signed with a competitor and might likely be 3 quarters out from renewal These signals are probably buried in your CRM. They’re not new to you. But when orchestrated right, they might be the fastest path to closing pipeline gaps. For the last 3 quarters, I've found that we haven't reinvented the wheel on   *what* campaigns drive pipeline, but we have reinvented the workflows that power them. What signals are you building workflows around to close pipeline gaps?