Clear definitions for every sales and marketing term you'll encounter — from ICP and signal-based selling to ABM, SDR, RevOps, and beyond.
A B2B strategy where sales and marketing align to target a specific list of high-value accounts rather than a broad market. Resources are concentrated on accounts most likely to close and generate the most revenue. ABM often combines personalised outreach, content, and advertising directed at key stakeholders within each target account.
Signal intelligence in GTMS →The salesperson responsible for closing new business. AEs own the full sales cycle from first discovery call through signed contract — they build relationships with decision-makers, run demos, negotiate terms, and hand off to customer success after close. In high-velocity teams, AEs receive qualified meetings from SDRs.
How AEs use GTMS →Any observable action that indicates a prospect is actively evaluating a solution or ready to make a purchase decision. Signals include visiting a pricing page, downloading a whitepaper, posting a relevant job opening, attending a product webinar, or engaging with competitor content. Signal-based selling prioritises outreach to prospects showing active signals over passive list-dialling.
Buying signals in GTMS →A role focused on pipeline generation through both inbound and outbound motions. BDRs qualify leads, research accounts, and book meetings for AEs. Some organisations use BDR and SDR interchangeably; in others, BDRs handle more strategic, higher-touch prospecting while SDRs work higher volumes.
BDR use cases →A structured, multi-step outreach sequence that defines the timing, channel, and content of each touchpoint with a prospect. A typical cadence might include a LinkedIn connection request, a personalised email, a follow-up call, and a final email — all spaced across 10-14 days. Cadences ensure consistent follow-up without relying on a rep's memory.
Sequences in GTMS →An unsolicited email sent to a prospect with whom the sender has no prior relationship. Effective cold emails are short, personalised, relevant to a specific pain point, and include a single clear call to action. Spray-and-pray templates rarely work; personalisation at scale — using prospect data and context — is what drives replies.
AI-written outreach in GTMS →A system of record for all interactions between a company and its customers and prospects. CRMs store contact data, deal stages, activity history, and pipeline forecasts. Common platforms include Salesforce, HubSpot, and Pipedrive. GTM tooling like GTMS syncs with CRMs to keep data current without manual entry.
CRM sync in GTMS →The process of appending additional data — firmographics, technographics, contact details, LinkedIn profiles, funding history — to a raw contact or company record. Enrichment transforms a name and email into a rich profile that sales reps can use to personalise outreach and prioritise their pipeline.
Contact enrichment in GTMS →The strategy and execution plan a company uses to bring a product or service to market and reach target customers. GTM encompasses pricing, positioning, distribution channels, sales motion (inbound vs. outbound), ICP definition, and marketing strategy. A GTM motion is considered 'working' when pipeline is predictable and repeatable.
GTMS platform overview →A detailed description of the company that would derive the most value from your product and that your business can serve best. An ICP is defined by firmographic attributes (industry, company size, revenue, geography) and sometimes technographic or behavioural attributes. Prospecting outside your ICP is one of the leading causes of low conversion rates and high churn.
ICP-fit scoring in GTMS →Behavioural signals that indicate a buyer is researching a category of solution. First-party intent comes from your own website and product (page views, free trial sign-ups). Third-party intent comes from external sources — review sites like G2, job postings, content consumption patterns, and social engagement. Combining intent sources dramatically improves prospecting precision.
Intent signals in GTMS →A numerical framework that ranks prospects by their likelihood to buy, usually combining fit (how closely they match the ICP) and intent (how actively they are signalling purchase readiness). Scores let revenue teams prioritise who to contact first and what cadence to enrol them in — hot leads get aggressive outreach, cool leads get nurturing.
AI lead scoring in GTMS →The use of software to execute LinkedIn outreach actions — connection requests, follow-up messages, InMails — at scale while staying within LinkedIn's rate limits. Effective LinkedIn automation pairs volume with personalisation: each message should reference something specific about the recipient rather than using a generic template.
LinkedIn automation in GTMS →A lead that marketing has determined is ready to pass to sales based on engagement behaviour — a demo request, a high lead score, or a specific action like downloading a pricing guide. The MQL definition should be agreed upon between marketing and sales to avoid leads being passed too early or too late.
Pipeline qualification in GTMS →The practice of engaging multiple stakeholders at the same target account simultaneously, rather than relying on a single champion. Multi-threading reduces deal risk because if one contact goes cold or leaves the company, the relationship continues through other contacts. Enterprise deals almost always require multi-threading to succeed.
Enterprise outreach in GTMS →Sales activity initiated by the seller rather than the buyer. Outbound includes cold email, cold calling, LinkedIn outreach, and social selling — all where the rep proactively reaches out to prospects. The effectiveness of outbound depends heavily on targeting quality (ICP fit + intent signals) and message personalisation.
Outbound automation in GTMS →The total value of deals at various stages of the sales process. Pipeline is the primary leading indicator of future revenue. A healthy pipeline has sufficient volume, appropriate stage distribution, and realistic conversion assumptions. 'Pipeline coverage' is the ratio of pipeline to quota — 3x coverage is a common target.
Pipeline analytics in GTMS →The process of identifying, researching, and initiating contact with potential customers. Traditional prospecting involves manually building lists and researching accounts. Modern prospecting layers intent signals, enrichment data, and AI personalisation on top of list-building to dramatically improve conversion rates.
AI prospecting in GTMS →An organisational function that aligns sales, marketing, and customer success operations under a shared data model, tooling stack, and process framework. RevOps teams own the CRM, define attribution models, manage the tech stack, and ensure data hygiene. The goal is to remove friction from the revenue process and improve forecasting accuracy.
Analytics & reporting in GTMS →A sales role focused exclusively on pipeline generation — identifying prospects, executing outreach, qualifying leads, and booking meetings for AEs. SDRs typically work high volumes of outbound activity measured by calls made, emails sent, and meetings booked. The SDR role is the most common entry point into a B2B sales career.
How SDR teams use GTMS →An automated, multi-step outreach campaign that sends a series of messages across one or more channels at predefined intervals. Sequences eliminate the manual task of follow-up and ensure every prospect receives a consistent experience. Modern sequences adapt dynamically — pausing automatically on reply, branching based on engagement, and personalising each message with prospect data.
Sequences in GTMS →The aggregation and analysis of behavioural, contextual, and relational signals to identify which prospects are most likely to buy and when. Signal intelligence goes beyond basic intent data to combine social activity, job postings, funding events, technology changes, and web behaviour into a unified account intelligence layer.
Signal intelligence in GTMS →A sales methodology that prioritises outreach based on real-time buyer signals rather than static lists or arbitrary cadence schedules. Instead of calling everyone on a list, signal-based sellers act when a prospect has shown meaningful intent — a pricing page visit, a job post for a relevant role, a competitor mention on LinkedIn. This dramatically increases connection rates and reply rates.
Signal-based selling with GTMS →A prospect that the sales team has confirmed matches the ICP and has demonstrated sufficient intent or need to warrant a sales conversation. SQLs typically come from MQLs that sales has reviewed, or from outbound prospecting where a rep has already done initial qualification. The MQL-to-SQL conversion rate is a key measure of marketing-to-sales alignment.
Pipeline qualification in GTMS →The total revenue opportunity available for a product or service if it achieved 100% market penetration. TAM analysis informs investor conversations, hiring plans, and go-to-market prioritisation. For sales teams, TAM translates into the maximum number of accounts that could ever be customers — helping set realistic pipeline targets.
Market intelligence in GTMS →Data about the technology stack a company uses — their CRM, marketing automation platform, cloud provider, analytics tools, and more. Technographic data helps sales teams identify tech stack compatibility, spot churning competitors, and personalise outreach around specific integrations or stack gaps.
Enrichment in GTMS →A business event that signals a prospect may be more receptive to outreach — a funding round, a new executive hire, a geographic expansion, a product launch, or a competitor churning. Trigger events are one of the highest-converting signals because they create a natural, timely reason to reach out.
Trigger events in GTMS →The process of gradually increasing the sending volume of a new email domain or address to build sender reputation with mail providers. Starting with low volumes and ramping up over 4-8 weeks prevents the domain from being flagged as spam. Skipping warm-up is one of the most common reasons cold email campaigns fail to land in inboxes.
Email deliverability in GTMS →The percentage of sales opportunities that result in a closed-won deal. Win rate is calculated by dividing closed-won deals by total closed deals (won + lost) in a period. Improving win rate through better ICP targeting, signal-qualified pipeline, and personalised outreach is often more impactful than increasing overall pipeline volume.
Pipeline analytics in GTMS →The use of software rules and triggers to automatically execute repetitive sales tasks — enrolling a new lead in a sequence, notifying an AE when a prospect replies, pausing outreach when a contact is flagged as out-of-office, or syncing data to a CRM. Workflow automation frees reps from administrative work and ensures no lead falls through the cracks.
Automation in GTMS →Sales teams often seek alternatives to ZoomInfo for contact data, enrichment, and intent signals. Modern alternatives prioritise real-time accuracy, intent layering, and AI-powered personalisation over raw database size. GTMS combines enrichment, signal intelligence, and outreach automation in a single platform — eliminating the need for separate prospecting and sequencing tools.
Compare GTMS vs ZoomInfo →Updated for modern signal-based GTM motions. More terms added regularly.
Browse the Academy →GTMS applies these concepts in one platform — signals, enrichment, sequences, and AI outreach.
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