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Marketing AdvertisingTop 10 Best Lead Scoring Software of 2026
Compare 10 lead scoring software tools for sales and marketing teams, with rankings, evaluation criteria, features, and tradeoffs.
How we ranked these tools
Core product claims cross-referenced against official documentation, changelogs, and independent technical reviews.
Analyzed video reviews and hundreds of written evaluations to capture real-world user experiences with each tool.
AI persona simulations modeled how different user types would experience each tool across common use cases and workflows.
Final rankings reviewed and approved by our editorial team with authority to override AI-generated scores based on domain expertise.
Score: Features 40% · Ease 30% · Value 30%
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HubSpot Marketing Hub is the strongest overall choice when marketing and sales need CRM-native scoring with workflow handoffs, while Salesforce Einstein Lead Scoring fits revenue teams already running an established Salesforce process and wanting machine-learning scores inside it.
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
HubSpot Marketing Hub
Separate contact and company score properties feed workflows, lists, CRM views, and owner assignment without exporting scoring data.
Built for fits when marketing and sales teams need CRM-native scoring with workflow-based handoffs..
Salesforce Einstein Lead Scoring
Editor pickPer-lead Einstein insights identify the specific positive and negative attributes driving each prediction inside Salesforce.
Built for fits when revenue teams need machine learning scores inside an established Salesforce sales process..
6sense
Editor pickRevenue AI links anonymous activity, third-party intent, and CRM data to predicted account buying stages.
Built for fits when enterprise revenue teams need account prioritization and coordinated sales and advertising workflows..
Related reading
Comparison Table
HubSpot Marketing Hub
SMB-to-mid-marketInbound marketing platform with native predictive and custom lead scoring.
Separate contact and company score properties feed workflows, lists, CRM views, and owner assignment without exporting scoring data.
HubSpot Marketing Hub lets administrators define positive and negative criteria using contact fields, company attributes, email activity, form submissions, page views, and custom events. Separate contact and company scores support both individual prioritization and account-level review. Workflow actions can update lifecycle stages, create tasks, assign owners, and notify sales representatives when conditions are met.
Configuration becomes more involved as teams add multiple score properties, business units, or exceptions across workflows. Score decay helps reduce the influence of older activity, but administrators must set appropriate intervals and exclusions. Inbound teams can use the resulting qualification data to trigger an MQL handoff with less manual list review.
- +Separate contact and company scores support account-aware prioritization
- +Workflow actions connect thresholds to owner assignment and notifications
- +Score decay reduces the influence of stale engagement
- +CRM APIs expose scoring records for connected applications
- –Complex scoring models require manual property and workflow governance
- –Advanced account prioritization needs separate contact and company configuration
- –Reporting depends on consistently maintained lifecycle and activity data
- –Many workflows can make score changes difficult to audit
Revenue operations teams
Align qualification thresholds across departments
Consistent qualification handoffs
B2B demand generation teams
Prioritize engaged target accounts
Clearer account prioritization
Show 2 more scenarios
Inbound marketing teams
Automate qualified contact follow-up
Faster sales follow-up
Workflows can send notifications, create tasks, and update records after contacts cross defined thresholds.
CRM administrators
Audit scoring inputs across workflows
Cleaner score governance
CRM properties and workflow history show the records, actions, and criteria affecting qualification.
Best for: Fits when marketing and sales teams need CRM-native scoring with workflow-based handoffs.
More related reading
Salesforce Einstein Lead Scoring
enterpriseAI-driven predictive lead scoring built into Salesforce Sales Cloud.
Per-lead Einstein insights identify the specific positive and negative attributes driving each prediction inside Salesforce.
Salesforce Einstein Lead Scoring fits organizations that already manage lead data and sales activity in Salesforce. Each lead receives a score from 1 to 99, while Einstein displays positive and negative factors behind the prediction. Administrators can use those fields in Salesforce views, reports, dashboards, and downstream automation.
The model depends on sufficient historical lead conversion data and does not replace a documented qualification policy. Teams with inconsistent field values or limited conversion history may receive less useful predictions. Salesforce account teams can combine the score with assignment rules and Flow-based lead routing after validating thresholds against actual sales outcomes.
- +Native scoring on Salesforce Lead records
- +Scores range from 1 to 99
- +Positive and negative score factors explain each prediction
- +Reports, dashboards, and list views expose score visibility
- –Prediction quality depends on historical conversion volume
- –Limited usefulness for teams with inconsistent lead fields
- –Custom business logic may require Salesforce Flow configuration
- –Salesforce administration is needed for field governance
Sales operations teams
Prioritize inbound sales queues
Faster queue prioritization
Marketing operations teams
Evaluate campaign-generated leads
Clearer campaign qualification
Show 1 more scenario
Revenue operations teams
Automate high-score assignment
Consistent lead distribution
Administrators combine Einstein scores with Salesforce Flow to assign qualified leads to designated representatives.
Best for: Fits when revenue teams need machine learning scores inside an established Salesforce sales process.
6sense
enterpriseAccount-based platform with predictive account and lead scoring models.
Revenue AI links anonymous activity, third-party intent, and CRM data to predicted account buying stages.
6sense can ingest first-party activity from CRM and marketing systems, then enrich account records with intent signals and buying-stage predictions. Salesforce and HubSpot connections support synchronized account and contact data, while APIs and workflow integrations expose segments and signals to downstream systems. Administrators can define segments, thresholds, and routing logic around an ideal customer profile.
The account-centric model is less suitable for teams that need transparent, contact-level point rules or detailed score decay controls. Data quality and identity resolution affect results, especially for smaller databases with limited web traffic. Enterprise revenue teams can use 6sense to coordinate sales outreach, advertising, and marketing workflows around named accounts.
- +Account-level predictions cover anonymous and known buyer activity.
- +Revenue AI combines first-party and third-party intent signals.
- +Salesforce and HubSpot integrations support CRM synchronization.
- +Segments feed advertising, sales alerts, and workflow automation.
- –Account-centric scoring offers limited transparency for contact-level qualification.
- –Identity resolution quality affects anonymous-visitor attribution.
- –Deployment requires substantial data, integration, and governance work.
- –Advanced orchestration depends on a mature revenue-operations process.
Revenue operations teams
Prioritize in-market accounts
Focused account prioritization
Enterprise sales teams
Route accounts by buying stage
More timely outreach
Show 1 more scenario
B2B marketing teams
Coordinate account advertising
Aligned account campaigns
Marketers build segments from predicted demand and activate them across advertising and campaign workflows.
Best for: Fits when enterprise revenue teams need account prioritization and coordinated sales and advertising workflows.
Microsoft Dynamics 365 Customer Insights
enterpriseCustomer data and journey software supports predictive and rules-based lead scoring.
Dataverse-backed unified profiles connect customer data, real-time journey triggers, and lead qualification within one Microsoft data model.
Microsoft Dynamics 365 Customer Insights combines unified customer profiles from Customer Insights - Data with real-time journey orchestration, giving lead scoring direct access to first-party behavioral and firmographic data. Teams can build rules-based scoring models from profile attributes and interaction events, then set a score threshold for qualification and handoff.
Dataverse, Dynamics 365 Sales, Power Automate, and REST APIs support CRM sync and downstream routing. The main tradeoff is administrative complexity across data unification, consent, security roles, and journey configuration.
- +Unified profiles combine Dataverse records with behavioral events before scoring.
- +Scoring models accept profile attributes, interactions, and custom business conditions.
- +Power Automate and Dataverse APIs support custom routing beyond built-in journeys.
- +Real-time journeys can trigger follow-up from forms, emails, events, and sales activity.
- –Data unification, consent, and security settings require coordinated administration across multiple workspaces.
- –Non-Microsoft CRM deployments need connector mapping and ongoing synchronization maintenance.
- –Lead qualification workflows are strongest inside Dynamics 365 Sales and Dataverse.
- –Reporting often requires Power BI or additional Dataverse configuration.
Best for: Fits when sales and marketing teams already use Dataverse and need unified-profile scoring tied to journeys.
Factors.ai
enterpriseB2B marketing intelligence software scores accounts using intent, engagement, and website activity.
Identity resolution links anonymous web visitors to company records before form fills or sales contact.
Factors.ai connects anonymous website visits to company records and prioritizes accounts using firmographic, technographic, behavioral, and intent signals. Account journeys, attribution reports, and buying-signal views show how activity accumulates across web, advertising, and campaign touchpoints. CRM and marketing integrations send identified activity into sales workflows, while custom event collection lets teams add first-party signals.
- +Associates unknown web sessions with company records.
- +Combines firmographic, technographic, behavioral, and intent signals in account views.
- +Account journeys connect web activity with campaign and advertising touchpoints.
- +Custom event collection supports first-party signals beyond standard page activity.
- –Individual contact qualification receives less emphasis than company-level prioritization.
- –Signal quality depends on accurate CRM and firmographic data.
- –Cross-system attribution requires consistent event naming and campaign tagging.
- –Full outbound sequencing still requires a separate sales engagement system.
Best for: Fits when B2B teams need anonymous visitor identification and account prioritization across channels.
LeanData
enterpriseRevenue orchestration software routes and qualifies leads using scoring, matching, and workflow rules.
Lead-to-account matching resolves incoming records against CRM accounts before routing executes.
LeanData fits Salesforce-centered revenue teams that need lead scores to trigger consistent ownership and follow-up. Its distinct capability is lead-to-account matching, which links incoming leads to existing account records before routing decisions run.
The visual routing builder supports round-robin assignment, territory rules, account ownership, and MQL handoff workflows. LeanData generally consumes scores from CRM or marketing systems rather than providing a standalone predictive scoring engine.
- +Lead-to-account matching preserves existing account ownership during inbound routing.
- +Visual graph builder exposes routing paths and fallback branches.
- +Salesforce actions update owners, queues, campaigns, and statuses immediately.
- +BookIt supports calendar-based meeting routing from forms and email.
- –Does not replace a dedicated predictive scoring engine.
- –Deep Salesforce dependence limits value for teams outside Salesforce.
- –Complex routing graphs require ongoing rule governance.
- –Scoring visibility depends on upstream CRM or marketing automation fields.
Best for: Fits when Salesforce teams need account-aware routing driven by existing lead scores.
Breadcrumbs
SMBRevenue intelligence software scores leads and accounts using customizable qualification models.
Revenue attribution connects scoring activity with campaign influence and pipeline outcomes.
Breadcrumbs combines rules-based scoring with revenue attribution, giving teams one workspace for qualification and funnel analysis. Scoring models can use person, company, and activity data, then send scores and segments to connected CRM and marketing systems.
Lead routing workflows and configurable thresholds support sales handoffs, while attribution reports connect campaigns with pipeline outcomes. Advanced predictive modeling and complex buying-group orchestration receive less coverage than in enterprise-focused products.
- +Combines lead scoring with multi-touch revenue attribution.
- +Scores contacts using person, company, and activity attributes.
- +Exports scores and segments to connected CRM and marketing systems.
- +Supports visual scoring rules without requiring custom code.
- –Predictive scoring is not the primary modeling approach.
- –Complex buying-group workflows receive less dedicated coverage.
- –Reliable scoring requires consistent data across integrations.
- –Attribution features add scope for teams needing qualification alone.
Best for: Fits when revenue teams need configurable qualification plus campaign-to-pipeline attribution in one application.
Demandbase
enterpriseDemandbase scores accounts and prospects using intent, firmographic, engagement, and advertising data.
Account identification connects anonymous website activity to company profiles before a known contact enters the CRM.
Demandbase centers scoring on accounts rather than isolated contacts, combining firmographic data, behavioral activity, and external intent signals to prioritize buying groups. Demandbase One connects anonymous website visits with company profiles and adds advertising, web personalization, sales intelligence, and pipeline orchestration around those records.
Its scoring can combine account engagement, fit attributes, intent, and predictive recommendations. Salesforce and marketing automation integrations transfer selected data into revenue workflows.
- +Demandbase identifies anonymous website visitors at the company level.
- +First-party engagement and third-party intent signals inform account prioritization.
- +Salesforce integration maps Demandbase account intelligence into seller workflows.
- +Advertising and web personalization use the same account audiences as sales activation.
- –Account-first scoring provides less detail for contact-level qualification queues.
- –Anonymous visitor matching depends on domain resolution and identifiable company traffic.
- –Cross-channel reporting requires careful configuration of account, contact, and campaign relationships.
- –Basic contact scoring is less central than Demandbase's account orchestration.
Best for: Fits when B2B revenue teams prioritize named accounts and intent signals over individual lead-volume scoring.
Zoominfo
B2B data and intent-driven account scoring platformZoominfo combines verified B2B company and contact data, buyer-intent signals, AI, and workflow automation to identify, prioritize, and route prospects most likely to convert.
Zoominfo can connect account-level buying activity to the specific people inside an organization who may influence the purchase, combining intent context, role and seniority information, organizational data, and automated workflows in one operating layer.
Zoominfo is a broad go-to-market intelligence platform for sales, marketing, and revenue operations teams rather than a standalone scoring utility. It combines company and contact records with firmographic, technographic, behavioral, and buyer-intent signals to help teams prioritize accounts and identify relevant decision-makers.
Its custom scoring models and workflow tools can filter prospects, trigger actions, discover contacts, and send records into CRM, sales-engagement, and marketing systems. The platform stands out by connecting account-level buying activity with specific people inside those accounts, giving teams more context for outreach and qualification.
- +Combines a large B2B contact and company database with firmographic and technographic filters.
- +Identifies specific people inside accounts showing buying interest instead of stopping at account-level activity.
- +Automates conditional workflows that can discover contacts, branch on criteria, and export records.
- +Pushes intent signals and enriched records into CRM, sales-engagement, and marketing platforms.
- –Zoominfo is broader and more operationally complex than a dedicated lead-scoring application.
- –The scoring experience emphasizes account intelligence and buying interest, so nuanced individual engagement models may require adjacent systems.
- –Workflow quality depends on accurate field mapping, filters, and downstream CRM configuration.
- –The platform's breadth can make score interpretation less transparent for teams seeking a simple single-score prospect queue.
Best for: B2B revenue teams that need prospect prioritization connected to a large business-data foundation, account research, buyer-interest monitoring, and automated activation across their existing sales and marketing stack.
Outfunnel
SMBOutfunnel tracks marketing engagement and assigns lead scores across connected sales and marketing tools.
CRM-linked scoring that combines website visits, email engagement, and form activity on individual contact records.
Outfunnel suits small sales teams that need marketing activity connected to an existing CRM without adopting a full marketing automation suite. Its lead scoring uses website visits, email engagement, and form activity to prioritize contacts.
CRM sync transfers engagement events and score changes into connected records. Coverage remains narrower than dedicated scoring systems because predictive models, account-level analysis, and advanced routing controls are limited.
- +Combines website tracking, email engagement, and form activity in one contact score.
- +Syncs engagement events and score changes with supported CRM records.
- +Provides a lighter setup than full marketing automation suites.
- +Supports practical prioritization for small sales pipelines.
- –Lacks predictive scoring based on large-scale historical conversion data.
- –Offers limited account-level analysis for complex B2B buying groups.
- –Provides fewer workflow and routing controls than enterprise platforms.
- –Integration coverage is narrower than major CRM marketing ecosystems.
Best for: Fits when small sales teams need CRM-linked engagement scoring without adopting a full marketing automation suite.
Conclusion
After evaluating 10 marketing advertising, HubSpot Marketing Hub stands out as our overall top pick — it scored highest across our combined criteria of features, ease of use, and value, which is why it sits at #1 in the rankings above.
Use the comparison table and detailed reviews above to validate the fit against your own requirements before committing to a tool.
How to Choose the Right lead scoring software
The guide compares HubSpot Marketing Hub, Salesforce Einstein Lead Scoring, 6sense, Microsoft Dynamics 365 Customer Insights, and Factors.ai across CRM integration, account signals, scoring controls, and workflow automation.
LeanData, Breadcrumbs, Demandbase, ZoomInfo, and Outfunnel complete the field with lead-to-account routing, attribution, anonymous visitor identification, business-data enrichment, and contact-level engagement scoring.
What Lead Scoring Software Measures and Automates
Lead scoring software assigns values to contacts, leads, or accounts from explicit attributes, behavioral events, intent signals, and conversion patterns. It can apply rules-based models or predictive models, maintain score history, and trigger qualification, routing, or CRM updates at a defined threshold.
HubSpot Marketing Hub separates contact and company score properties, then sends thresholds into workflows, CRM views, and owner assignment. Salesforce Einstein Lead Scoring predicts a score from 1 to 99 and shows the positive and negative lead attributes behind each prediction inside Salesforce.
Lead Scoring Capabilities That Separate These Platforms
Integration depth determines whether scores remain visible in CRM records and usable in downstream workflows. HubSpot Marketing Hub and Salesforce Einstein Lead Scoring keep scoring inside their native CRM environments, while Outfunnel writes engagement events to supported CRM contact records.
Account coverage changes how revenue teams prioritize buying activity. 6sense, Factors.ai, Demandbase, and ZoomInfo connect anonymous activity or intent signals to company records, while Breadcrumbs adds campaign influence and pipeline attribution to qualification.
Contact and company score architecture
HubSpot Marketing Hub maintains separate contact and company score properties for CRM views, workflows, and owner assignment. 6sense predicts account buying stages from anonymous activity, third-party intent, and CRM signals instead of centering qualification on individual contacts.
Predictive explanations and model inputs
Salesforce Einstein Lead Scoring produces scores from 1 to 99 and identifies the positive and negative lead attributes behind each prediction. Microsoft Dynamics 365 Customer Insights accepts profile attributes, interactions, and custom business conditions within Dataverse.
Anonymous visitor and intent resolution
Factors.ai links anonymous web visitors to company records before a form fill or sales interaction. Demandbase identifies anonymous website activity at the company level and combines first-party engagement with third-party intent.
Routing and workflow execution
LeanData matches incoming leads to Salesforce accounts before routing and exposes fallback branches in a visual graph builder. HubSpot Marketing Hub connects score thresholds to owner assignment and notifications through workflow actions.
Attribution and business-data enrichment
Breadcrumbs connects scoring activity with campaign influence and pipeline outcomes through multi-touch revenue attribution. ZoomInfo combines firmographic and technographic filters with contact intelligence, buyer-interest monitoring, and automated activation.
Choose the Scoring Model, Data Scope, and Automation Layer
The right selection depends on the object being prioritized, the signals available to the model, and the system that executes follow-up. Contact scoring, account intelligence, predictive modeling, and routing each require different records, integrations, and administrative controls.
Teams should also separate scoring from adjacent functions. LeanData handles Salesforce routing rather than replacing a predictive engine, while Breadcrumbs combines qualification with attribution and Outfunnel focuses on contact engagement without a full marketing automation suite.
Choose contact qualification or account prioritization
Select HubSpot Marketing Hub, Salesforce Einstein Lead Scoring, or Outfunnel when sales queues depend on individual contact records. Select 6sense, Factors.ai, Demandbase, or ZoomInfo when anonymous activity, intent, and buying-group context matter more than a single contact score.
Choose rules-based control or predictive modeling
Choose Microsoft Dynamics 365 Customer Insights when teams need custom business conditions across unified profiles and interactions. Choose Salesforce Einstein Lead Scoring when historical conversion patterns can support machine learning predictions with per-lead explanations.
Verify the system that owns the customer record
HubSpot Marketing Hub keeps contact and company scores in its CRM properties, while Microsoft Dynamics 365 Customer Insights uses Dataverse profiles. LeanData depends deeply on Salesforce, and non-Microsoft CRM deployments require connector mapping and synchronization maintenance with Dynamics 365 Customer Insights.
Separate score generation from routing execution
Choose LeanData when the main requirement is lead-to-account matching and Salesforce path control after a score exists. Choose HubSpot Marketing Hub when score thresholds must directly trigger owner assignment, notifications, lists, and CRM views.
Decide whether attribution belongs in the same application
Choose Breadcrumbs when campaign influence and pipeline outcomes must sit beside configurable qualification. Choose Outfunnel when the requirement is website, email, and form engagement on individual CRM contacts without adding attribution workflows.
Teams That Benefit From Specific Lead Scoring Architectures
CRM-native teams benefit from score properties, record-level visibility, and workflow actions that connect qualification to ownership. HubSpot Marketing Hub and Salesforce Einstein Lead Scoring place those controls directly inside established sales processes.
B2B account teams need a different operating model when anonymous sessions, intent signals, and multiple stakeholders shape a purchase. 6sense, Factors.ai, Demandbase, and ZoomInfo prioritize company context, while LeanData addresses the routing step after account matching.
Marketing and sales teams using HubSpot CRM
HubSpot Marketing Hub separates contact and company scores and sends thresholds into workflows, lists, CRM views, and owner assignment. The structure supports account-aware prioritization without exporting scoring properties.
Revenue teams with established Salesforce lead processes
Salesforce Einstein Lead Scoring places machine learning scores on Salesforce Lead records and exposes the attributes influencing each prediction. LeanData suits the same environment when account matching and routing are the primary gaps.
Enterprise account-based revenue teams
6sense connects anonymous activity, third-party intent, and CRM records to predicted account buying stages. Factors.ai and Demandbase also identify company-level activity before an individual contact becomes known.
Microsoft-centered sales and marketing operations
Microsoft Dynamics 365 Customer Insights connects Dataverse records, behavioral events, profile conditions, and journey triggers in one Microsoft data model. Its administration requires coordinated data unification, consent, and security settings.
Small sales teams needing contact engagement signals
Outfunnel combines website visits, email engagement, and form activity on individual CRM contacts. It provides a narrower operating layer than ZoomInfo, which combines buying interest with a large business-data and activation platform.
Common Lead Scoring Selection and Deployment Errors
A score can look precise while missing the record type, signals, or historical volume required for useful qualification. Salesforce Einstein Lead Scoring depends on consistent lead fields and sufficient conversion history, while 6sense and Demandbase depend on accurate identity resolution for anonymous activity.
Operational errors also occur when score generation, routing, attribution, and CRM administration are treated as one function. LeanData routes matched records but does not replace a dedicated predictive engine, and Breadcrumbs adds attribution that account-first platforms do not provide.
Choosing account intelligence for a contact-level qualification queue
6sense, Demandbase, and Factors.ai emphasize company activity and account prioritization. Salesforce Einstein Lead Scoring or Outfunnel is better suited to queues built around individual lead or contact records.
Deploying predictive scoring without usable conversion history
Salesforce Einstein Lead Scoring needs sufficient historical conversion volume and consistent lead fields. Teams with sparse or inconsistent records should use explicit rules in HubSpot Marketing Hub or custom conditions in Microsoft Dynamics 365 Customer Insights.
Treating anonymous visitor matching as individual identification
Factors.ai and Demandbase resolve anonymous web activity primarily to company profiles. Domain resolution and identifiable company traffic affect attribution, so individual contact qualification should not be assumed before a known person enters the CRM.
Buying a routing tool to replace score generation
LeanData matches leads to Salesforce accounts and executes routing paths after records enter the CRM. It does not replace a predictive scoring engine, so a separate model is required when qualification predictions are the core requirement.
Ignoring governance for fields, workflows, and synchronized records
HubSpot Marketing Hub requires coordinated contact and company properties plus workflow rules for complex models. Microsoft Dynamics 365 Customer Insights also requires administration across data unification, consent, security, and connector synchronization.
How We Selected and Ranked These Tools
We evaluated HubSpot Marketing Hub, Salesforce Einstein Lead Scoring, 6sense, Microsoft Dynamics 365 Customer Insights, Factors.ai, LeanData, Breadcrumbs, Demandbase, Zoominfo, and Outfunnel across scoring features, ease of use, and value. Features accounted for 40% of each overall score, while ease of use accounted for 30% and value accounted for 30%.
HubSpot Marketing Hub scored 9.7 For features, 9.3 For ease, and 9.2 For value. HubSpot Marketing Hub ranked first because separate contact and company score properties connect CRM visibility, workflow automation, and owner assignment in one operating layer.
Frequently Asked Questions About lead scoring software
How do predictive and rules-based lead scoring differ across the listed tools?
How do lead scores trigger CRM workflows and sales handoffs?
Which tools score accounts instead of only individual contacts?
When should a team choose Salesforce Einstein Lead Scoring over HubSpot Marketing Hub?
How do APIs and integrations extend lead scoring workflows?
What security and administration controls should buyers evaluate?
How can a team migrate existing scoring data into a new platform?
What breaks if scoring depends on anonymous intent or website identity resolution?
Which lead scoring software suits a small sales team with an existing CRM?
Tools reviewed
Primary sources checked during evaluation.
Referenced in the comparison table and product reviews above.
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