DiscoLike v2: Features on Every Plan
DiscoLike v2 includes tech stack targeting, segmentation, API access, and CRM integrations on every plan. See email verification and usage distinctions.
Waterfall Enrichment: Coverage and Data Quality
Evaluate waterfall enrichment by verified incremental coverage, source overlap, and cost. Learn why a filled contact field is not proof of fresh data.
ContaGen: Contact Discovery Beyond LinkedIn
Find business contacts beyond standard databases with ContaGen. Learn the open-web workflow, evidence checks, and model and search cost considerations.
How to Evaluate B2B Data Sources
Evaluate B2B data sources by provenance, freshness, and fit. Learn when company websites, directories, and aggregators help build better account lists.
DiscoLike MCP: Refine Your ICP Query Plan
Inspect and refine ICP query plans with DiscoLike MCP. Review semantic text, phrase matches, and filters before running a larger target account search.
DiscoGen: A Claygent Alternative with BYOK
Compare DiscoGen as a Claygent alternative for company research. Bring model and search keys, use company context, and measure cost per verified answer.
DiscoGen BYOK: Model and Search API Keys
Learn how DiscoGen BYOK separates model, search, and platform costs. Use company context, compare providers, and budget AI research per accepted result.
Outcome Learning Models for SaaS Products
Learn how outcome learning models turn successful SaaS workflows into better guidance. See DiscoLike’s query assistant example and the limits of feedback.
Hybrid AI Search for Company Discovery
Learn how hybrid AI search combines semantic retrieval and keyword constraints for company discovery. Build an ICP query, review matches, and refine the plan.
AI TAM Query Assistant for ICP Search
Turn a rough ICP description into a company search with DiscoLike’s AI TAM Query Assistant. Review the suggested text, phrase matches, and filters.
Why Clay Grew: GTM Workflow Integration
Explore Clay’s appeal as a GTM integration layer and how agent workflows change the tradeoffs. Separate orchestration choices from company data quality.
Find B2B Contacts by Career Experience
Find B2B contacts by responsibilities and career experience with natural language persona search. Learn how to define a role and validate relevant matches.
Claude Code and MCP for GTM Workflows
See how Claude Code and DiscoLike MCP can segment customer lists and find lookalike accounts. Learn where conversational workflows still need checks.
Can Gemini Estimate B2B Website Traffic?
Can Gemini replace Similarweb for B2B traffic estimates? Learn what public search can support, why tags do not reveal visits, and how to verify numbers.
Search Grounding APIs for GTM Research
Use search grounding APIs for GTM company research with current sources and citations. Learn how to specify evidence, dates, and unknowns in each task.
Job Title Variations in B2B Contact Search
Find contacts across job title variations without maintaining endless keyword lists. See an IT support example and learn how to review semantic matches.
Vector Search for People and Career Patterns
Explore vector search for people using career descriptions and responsibilities. Learn how to express professional experience and review semantic matches.
Ecommerce Prospecting with Missing Signals
Find ecommerce prospects using missing technology and website signals. Learn how to turn absent pixels, social links, and features into research questions.
DiscoLike API Access on Every Plan
Use DiscoLike API access on every paid plan for company discovery, enrichment, and domain matching. Learn how to start with a bounded integration test.
Use ICP Research Across Your GTM Tools
Create an ICP description and targeting vocabulary in DiscoLike, then use the research across your GTM tools. Check how each system interprets the criteria.
Structured Prompts for GTM Data Workflows
Write structured prompts for GTM data workflows with explicit inputs, decision rules, evidence, and output fields. Includes an ICP validation example.
AI Account Signals: Research the Public Web
Use AI to research public account signals such as hiring, funding, and expansion. Build prompts that return dated evidence, source URLs, and unknowns.
Combine Vector Search and Exact Phrase Match
Combine vector search and exact phrase matching to find specialized accounts. A hospital example shows how business fit and explicit evidence work together.
Build a Reliable B2B Company Data Foundation
Build a B2B company data foundation before adding GTM automations. Learn how domain identity, source coverage, and validation reduce fragmented workflows.
Micro TAMs: Finding Fewer Than 100 Accounts
Build a micro TAM when fewer than 100 accounts may qualify. Define the market, combine sources, verify every candidate, and track unresolved coverage gaps.
How to Find Companies in Niche Industries
Find companies in niche industries with precise ICP descriptions, seed domains, and evidence-based validation. Includes examples and a qualification prompt.
Find Accounts Your B2B Database Misses
Find gaps in your B2B account database with website-based discovery, richer research context, and verified technology signals. Start with a coverage audit.
DiscoGen: AI Company Research with Context
Run AI company research with DiscoGen using firmographics and homepage text. Build research columns, control web search, and validate supporting evidence.
Usage-Based Pricing Risks for GTM Tools
Compare usage-based pricing with flexible credit subscriptions for GTM tools. Learn how to budget bulk jobs, control retries, and avoid unexpected spend.
Google Maps Coverage for Local Prospecting
Compare Google Maps and website-based data for local prospecting. A three-city dentist example shows why geography and validation affect coverage.
3 GTM Data Problems to Solve Before Automation
Solve inbound domain cleanup, customer segmentation, and company-name matching before building GTM automations. Learn the checks each workflow needs.
Google Maps Prospecting at National Scale
Plan Google Maps prospecting beyond a local demo. Account for geographic retrieval, deduplication, website extraction, and qualification across a national list.
Context Engineering for Account Discovery
Build better account discovery queries with a clear ICP brief, sample customers, hard filters, and website evidence. Includes a practical prompt example.
B2B Intent Signals in the Age of AI Agents
Learn how AI activity complicates B2B intent signals and how to prioritize accounts using business fit, website evidence, and verified buying context.
Why AI Prompts Break GTM Automations
Fix inconsistent AI results in GTM automations by separating retrieval, generation, and validation. Learn which checks make account workflows repeatable.
Finding Golf Clubs Beyond LinkedIn
A DiscoLike search found 6,487 US golf clubs, but only 1,181 had a LinkedIn link. See how to test company coverage beyond your existing prospecting list.
Use Subdomains as B2B Growth Signals
Use subdomains to research company growth and business functions. Learn what app, support, and blog domains can reveal and how to validate the signal.
Fix Data Gaps in Clay and n8n Workflows
Improve Clay and n8n prospecting workflows by fixing missing accounts and poor website inputs before AI qualification. Follow a practical data-first process.
ColdIQ TAM Mapping: 2,000 New Accounts
How ColdIQ used DiscoLike for enterprise TAM mapping, adding 2,000 qualified accounts and 15,000 contacts with lookalike search and Clay validation.
Audit B2B Data Accuracy and Market Coverage
Audit B2B data with a 100-record sample and an independent comparison list. Measure account accuracy, net-new coverage, and gaps without overstating TAM.
TAM Mapping with Hard-to-Verify Criteria
A fintech and mobile-app TAM example shows how to separate searchable criteria from proxies. Build a candidate list, then verify MAU and technology fit.
Find SaaS Companies with Website Signals
Find SaaS companies by combining demo and trial phrases, vendor signals, and size filters. Validate the results when lookalike search returns adjacent firms.
Website Signals for B2B Account Targeting
Target B2B accounts using website phrases, certifications, partner mentions, and calls to action. Learn how to combine signals and validate their meaning.
Find Companies Using a Specific Technology
Find companies using a vendor with technographic signals, then combine business fit and geography. Learn what a detection proves and what needs checking.
Handle Exclusions in AI Account Search
Handle exclusions in AI account search with explicit domain lists, phrase filters, and validation. Learn why adding “not” to an ICP description can fail.
Google AI Mode SEO: Clear Company Positioning
Improve company positioning for Google AI Mode with clear category language, specific use cases, and useful evidence. Avoid unsupported ranking shortcuts.
Website Differentiation and Semantic Search
Make your website distinct in semantic search with specific products, use cases, and customer evidence. Learn what similarity comparisons can tell you.
AI Target Account Lists: Build and Validate
Build AI target account lists from indexed company records. Learn how to separate discovery, research, deduplication, and validation before exporting.
AI-Generated Websites and B2B Data Quality
Protect B2B data quality as AI-generated websites become easier to create. Check business identity, source consistency, and evidence before accepting accounts.
AI-Generated Code: The Cost of Maintenance
Understand the maintenance cost of AI-generated code in GTM workflows. Review ownership, failure handling, and validation before shipping an automation.
Reliable AI Customer Segmentation and Counts
Keep AI customer segmentation accurate with persistent record IDs, deterministic counts, and explicit checks. Separate useful labels from data integrity.
Choosing AI Models for High-Volume Data Work
Choose AI models for high-volume data work by measuring cost, accuracy, and review effort. Learn where specialized models and retrieval fit a GTM pipeline.
Innovation Selling for B2B Sales Teams
Make B2B sales outreach more useful by leading with a specific new capability, customer evidence, and a testable offer instead of generic pain points.
LinkedIn Data Limits for B2B Prospecting
Evaluate LinkedIn-derived data for B2B prospecting by checking permitted use, freshness, and market coverage. Learn how website-based discovery complements it.
Semantic Search vs Keywords for B2B Discovery
Compare semantic search and keyword matching for B2B company discovery. Learn how embeddings, exact phrases, and clear ICP descriptions work together.
Target Account Modeling: A Practical Guide
Build a target account model from customer segments, lookalike searches, and validation. Learn how to define your ICP, size a segment, and measure coverage.
