{"id":9175,"date":"2026-09-24T05:02:38","date_gmt":"2026-09-24T05:02:38","guid":{"rendered":"https:\/\/www.coffee.ai\/articles\/sales-stack-consolidation-alternatives"},"modified":"2026-09-24T05:02:38","modified_gmt":"2026-09-24T05:02:38","slug":"sales-stack-consolidation-alternatives","status":"publish","type":"post","link":"https:\/\/www.coffee.ai\/articles\/sales-stack-consolidation-alternatives","title":{"rendered":"Sales Stack Consolidation Alternatives: A Decision Guide"},"content":{"rendered":"<p><em>Written by: Doug Camplejohn, CEO &amp; Co-Founder, Coffee<\/em><\/p>\n<h2>What Is a Sales Stack?<\/h2>\n<p>A sales stack is the collection of software tools a revenue team uses across the deal lifecycle, including CRM, prospecting, enrichment, engagement, conversation intelligence, and forecasting. <a href=\"https:\/\/syncgtm.com\/blog\/how-many-tools-do-b2b-sales-professionals-use\" target=\"_blank\" rel=\"noindex nofollow\">Most B2B teams run 8\u201312 tools, with only 3\u20136 used daily.<\/a><\/p>\n<h2 id=\"key-takeaways\">Key Takeaways for Choosing a Consolidation Path<\/h2>\n<ul>\n<li>Consolidation is a sequencing decision, where selecting the right architectural layer matters more than choosing a specific vendor.<\/li>\n<li>The six consolidation architectures each consolidate different layers and fit distinct team profiles, from SMBs under 50 reps to teams over 75 reps with complex workflows.<\/li>\n<li>Consolidating the intelligence and data-entry layer first removes the root cause of fragmented stacks without forcing a risky CRM migration.<\/li>\n<li>The AI-agent layer gives SMBs and mid-market teams a flexible path by consolidating the labor of data entry, enrichment, prospecting, meeting intelligence, visitor identification, and outreach without a CRM migration.<\/li>\n<li>Coffee is the AI-agent layer architecture for sales stack consolidation, working either as a standalone AI-first CRM or as a companion app that feeds Salesforce and HubSpot.<\/li>\n<\/ul>\n<p><a href=\"https:\/\/www.coffee.ai\/pricing\" class=\"solid-button\" target=\"_blank\">See How Coffee Consolidates Your Stack<\/a><\/p>\n<h2>The Six Sales Stack Consolidation Alternatives<\/h2>\n<h3>All-in-One CRM for Small Teams<\/h3>\n<p>This architecture consolidates CRM, email sequencing, and lead management into a single vendor. It replaces standalone sequencers and separate marketing point solutions. The primary example is HubSpot Sales Hub. <a href=\"https:\/\/abmatic.ai\/blog\/revenue-operations-tech-stack-guide\" target=\"_blank\" rel=\"noindex nofollow\">SMBs under 50 employees typically use all-in-one platforms, which are faster to implement but less flexible than best-of-breed alternatives.<\/a> The tradeoff is a customization ceiling that becomes visible as teams scale past 150 reps or introduce complex CPQ requirements.<\/p>\n<h3>CRM Plus Specialists for Established Workflows<\/h3>\n<p>This architecture keeps the CRM as the system of record and connects specialist tools via APIs. It adds an integration layer on top of existing point solutions rather than replacing them. A common configuration is Salesforce plus Marketo, Looker, and 6sense. <a href=\"https:\/\/revenue.io\/blog\/how-many-sales-tools-does-your-team-actually-need\" target=\"_blank\" rel=\"noindex nofollow\">Each tool-to-CRM integration costs $5,000\u2013$15,000 per year in direct and indirect maintenance costs, so a five-tool stack creates five potential failure points and five recurring cost centers.<\/a> This architecture fits mid-market teams with complex, established workflows that cannot tolerate disruption.<\/p>\n<h3>Revenue Platform for Unified Selling and Forecasting<\/h3>\n<p>This architecture unifies the engagement and intelligence layers, replacing separate forecasting and conversation intelligence tools. The defining example is the Salesloft-Clari combined platform. The two companies merged in December 2025 and rebranded under the Salesloft name on September 1, 2026. Salesloft positions the result as one system that connects selling and forecasting end to end, and claims no other vendor owns both the engagement layer and the intelligence layer integrated rather than bolted together. This architecture suits teams that want unified selling and forecasting without managing separate vendor relationships for each layer.<\/p>\n<h3>Best-of-Breed for Category Depth<\/h3>\n<p>This architecture also keeps the CRM as the system of record and connects specialist tools through APIs, with a deliberate emphasis on category depth over integration simplicity. A representative configuration is Salesforce CRM plus Gong, Clari, and ZoomInfo. <a href=\"https:\/\/revenue.io\/blog\/how-many-sales-tools-does-your-team-actually-need\" target=\"_blank\" rel=\"noindex nofollow\">Teams over 75 reps may benefit from best-of-breed in specific categories like enablement and data enrichment while consolidating the core execution stack.<\/a> The integration and administration overhead is highest in this model.<\/p>\n<h3>Warehouse-Centric for Advanced Analytics<\/h3>\n<p>This architecture pulls data from all revenue tools into a data warehouse for unified reporting, replacing reporting fragmentation rather than the point solutions themselves. Examples include Snowflake or BigQuery with reverse ETL. <a href=\"https:\/\/pedowitzgroup.com\/blog\/revops-tech-stack-blog\" target=\"_blank\" rel=\"noindex nofollow\">A dedicated data warehouse makes sense only when pulling data from 10 or more sources, needing sub-second query performance for operational dashboards, or having a BI team requiring SQL access.<\/a> It adds an architectural layer to manage and fits teams with dedicated data engineering resources.<\/p>\n<h3>AI-Agent Layer for Labor Consolidation<\/h3>\n<p>This architecture deploys an AI agent either as a companion app on top of an existing CRM or as a standalone AI-first CRM. It consolidates data entry, enrichment, prospecting, meeting intelligence, visitor identification, and outreach into a single agent. Examples include Coffee and Salesforce Agentforce. <a href=\"https:\/\/unite.ai\/salesforce-debuts-job-ready-agentforce-agents-and-long-horizon-runtime\" target=\"_blank\" rel=\"noindex nofollow\">Salesforce&#8217;s September 2026 Agentforce launch introduced job-ready agents built directly into Customer 360, with the company reporting 7 billion Agentic Work Units delivered across Agentforce and Slack, including 3.2 billion in Q2 2026 alone.<\/a> This architecture gives SMBs and mid-market teams a flexible consolidation path because it delivers value without a CRM migration.<\/p>\n<figure style=\"text-align: center\"><a href=\"https:\/\/www.coffee.ai\/pricing\" target=\"_blank\"><img decoding=\"async\" src=\"https:\/\/cdn.aigrowthmarketer.co\/1763678549697-4e8d65abe17d.gif\" alt=\"GIF of Coffee platform where user is using AI to prep for a meeting with Coffee AI\" style=\"max-height: 500px\" loading=\"lazy\"><\/a><figcaption><em>Automated meeting prep with Coffee AI CRM Agent<\/em><\/figcaption><\/figure>\n<h2>Sales Stack Consolidation Alternatives Compared<\/h2>\n<p>The table below shows why these six architectures are not interchangeable. Each one consolidates a different layer of the stack, so the right choice depends on where fragmentation hurts most. Read down the \u201cLayers Consolidated\u201d column to see how each option tackles a different problem.<\/p>\n<table>\n<thead>\n<tr>\n<th>Architecture<\/th>\n<th>Layers Consolidated<\/th>\n<th>Point Solutions Replaced<\/th>\n<th>Best Fit<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>All-in-One CRM<\/td>\n<td>CRM, email sequencing, lead management<\/td>\n<td>Standalone sequencers, separate marketing point solutions<\/td>\n<td>SMBs under 50 employees wanting one vendor<\/td>\n<\/tr>\n<tr>\n<td>CRM Plus Specialists<\/td>\n<td>CRM as system of record, integration layer for specialist tools<\/td>\n<td>None, focuses on centralizing integrations<\/td>\n<td>Mid-market teams with complex workflows<\/td>\n<\/tr>\n<tr>\n<td>Revenue Platform<\/td>\n<td>Engagement and intelligence layers<\/td>\n<td>Separate forecasting and conversation intelligence tools<\/td>\n<td>Teams wanting unified selling and forecasting<\/td>\n<\/tr>\n<tr>\n<td>Best-of-Breed<\/td>\n<td>CRM as system of record, deep specialist tools via APIs<\/td>\n<td>None, prioritizes category depth over consolidation<\/td>\n<td>Teams over 75 reps needing category depth<\/td>\n<\/tr>\n<tr>\n<td>Warehouse-Centric<\/td>\n<td>Data from all revenue tools into warehouse<\/td>\n<td>Reporting fragmentation<\/td>\n<td>Teams with 10+ data sources and BI teams<\/td>\n<\/tr>\n<tr>\n<td>AI-Agent Layer<\/td>\n<td>Data entry, enrichment, prospecting, meeting intelligence, visitor identification, outreach<\/td>\n<td>Apollo, ZoomInfo, Gong, Outreach, Salesloft, RB2B, Warmly<\/td>\n<td>SMBs and mid-market teams wanting agent-led consolidation<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>The Sequencing Thesis: Consolidate the Intelligence Layer First<\/h2>\n<p>With all six architectures on the table, the next decision is where to start. The most defensible consolidation recommendation starts with the intelligence and data-entry layer rather than the CRM. This layer includes contact databases, intent providers, AI research tools, and meeting intelligence platforms that feed the CRM. Overlap is highest here, data decays fastest, and rep time is most visibly wasted.<\/p>\n<p>The root cause of a fragmented sales stack is the data-entry burden that fragmentation creates, not the tooling count itself. Reps toggling between HubSpot, ZoomInfo, Salesloft, and Gong lose focus and create data gaps every time they fail to log an interaction. <a href=\"https:\/\/nektar.ai\/crm-data-entry\" target=\"_blank\" rel=\"noindex nofollow\">79% of opportunity-related activity data never makes it into the CRM at all, largely because manual entry is structurally unreliable at the volume and pace modern selling requires.<\/a><\/p>\n<p>22.5% of B2B data goes bad each year, meaning a database of 10,000 contacts could have more than 2,000 inaccurate records within 12 months. That decay accelerates when data lives across multiple disconnected systems. <a href=\"https:\/\/revenue.io\/blog\/how-many-sales-tools-does-your-team-actually-need\" target=\"_blank\" rel=\"noindex nofollow\">Context switching costs 15\u201325 minutes of productive time per switch, so a rep using five tools throughout the day can lose over an hour to switching alone.<\/a><\/p>\n<p>Consolidating the intelligence layer first, before touching the CRM, removes the data-entry root cause without triggering a risky system-of-record migration. Once the intelligence layer is clean and automated, replacing the CRM becomes a strategic choice instead of an urgent fix.<\/p>\n<h2>When Consolidation Means Replacing Salesforce vs. Keeping It<\/h2>\n<p>Many Salesforce-focused teams want to know whether consolidation requires ripping out the CRM. For most mid-market teams, the answer is no, at least in the early stages.<\/p>\n<p>The companion-app model positions an AI agent as a layer on top of an existing Salesforce or HubSpot instance. The agent handles data entry, enrichment, meeting intelligence, and outreach while the CRM remains the system of record. This approach delivers consolidation value while avoiding the adoption risk and data migration complexity of a full CRM replacement.<\/p>\n<p><a href=\"https:\/\/crn.com\/news\/ai\/2026\/salesforce-dreamforce-2026-ceo-benioff-touts-new-aiforce-interface-layer\" target=\"_blank\" rel=\"noindex nofollow\">Salesforce&#8217;s Agentforce architecture, including the AIforce interface layer announced at Dreamforce 2026, positions the agent layer as a front door over the underlying system of record and data layer.<\/a> This market signal shows that even Salesforce frames the agent as a companion to the CRM rather than a substitute.<\/p>\n<p>Full CRM replacement makes sense when the existing system carries so much legacy configuration debt that the agent cannot write clean data back to it. Replacement also fits when the team is small enough that migration risk is low and the cost of maintaining two systems exceeds the cost of switching.<\/p>\n<h2>Will AI Agents Replace Your CRM, or Consolidate on Top of It?<\/h2>\n<p>The AI-agent layer functions as a first-class consolidation architecture in its own right. The distinction matters because the agent layer consolidates the work of data entry, enrichment, research, meeting preparation, and outreach, which is the labor layer rather than the record layer.<\/p>\n<p>That 7 billion Agentic Work Units figure cited earlier shows that agentic execution at scale has moved beyond pilot-stage experiments. The market is shifting from AI that only answers questions to AI that actually does work.<\/p>\n<p>Coffee operates in this architecture as both a standalone AI-first CRM and as a companion app that feeds Salesforce and HubSpot. In the standalone model, the Coffee Agent is the system of record. In the companion model, the agent handles the intelligence and data-entry layer while the existing CRM retains its role as the record-keeping foundation. Both models deliver the same core outcome: reliable data in and reliable data out, without turning reps into data entry clerks.<\/p>\n<figure style=\"text-align: center\"><a href=\"https:\/\/www.coffee.ai\/pricing\" target=\"_blank\"><img decoding=\"async\" src=\"https:\/\/cdn.aigrowthmarketer.co\/1763678321672-5c8717cf0024.gif\" alt=\"Create instant meeting follow-up emails with the Coffee AI CRM agent\" style=\"max-height: 500px\" loading=\"lazy\"><\/a><figcaption><em>Create instant meeting follow-up emails with the Coffee AI CRM agent<\/em><\/figcaption><\/figure>\n<p><a href=\"https:\/\/www.coffee.ai\/pricing\" class=\"solid-button\" target=\"_blank\">Try the AI-Agent Layer<\/a><\/p>\n<h2>When Not to Consolidate Your Sales Stack<\/h2>\n<p>Consolidation does not fit every situation. Three specific scenarios favor best-of-breed instead:<\/p>\n<ul>\n<li><strong>Regulated industries.<\/strong> Healthcare and financial services organizations subject to multi-year security reviews often cannot absorb the vendor change risk that consolidation introduces. The compliance overhead of validating a new system can exceed the productivity gain.<\/li>\n<li><strong>Complex custom Salesforce workflows.<\/strong> Teams with deeply customized Salesforce instances, including custom objects, territory management, CPQ configurations, and multi-org setups, face integration complexity that can make consolidation more expensive than the status quo. The phrase \u201cwe replaced 10 tools with one and now we are stuck\u201d usually describes a team that consolidated before auditing its Salesforce dependencies.<\/li>\n<li><strong>Best-of-breed conversation intelligence requirements.<\/strong> Teams that rely on Gong&#8217;s category-depth analytics, such as multi-language transcription, tracker configuration, and coaching workflows, may find that consolidating conversation intelligence into a general-purpose agent sacrifices capability that directly affects rep performance and deal outcomes.<\/li>\n<\/ul>\n<h2>How to Consolidate Your Sales Stack in 30 Days<\/h2>\n<p>If none of those three situations apply, the shadow-pilot approach gives you the lowest-risk path to a consolidation decision. Pick one consolidated workflow, usually inbound lead handling or post-meeting follow-up, and run the new system in parallel on that workflow for two to four weeks. Keep the rest of the stack unchanged during this period.<\/p>\n<p><a href=\"https:\/\/digitalsalespro.net\/articles\/b2b-sales-tech-stack-consolidation-guide-2026\" target=\"_blank\" rel=\"noindex nofollow\">Running new consolidated platforms alongside legacy tools for at least two to four weeks gives reps time to adapt while maintaining a safety net, and auditing a random sample of records verifies data migration accuracy before you move past the parallel-environment phase.<\/a><\/p>\n<p>Before the pilot starts, define what success looks like so the decision does not come down to subjective impressions. The qualitative measures, such as data completeness on the records the agent touches, rep time reclaimed from manual entry, and integration count reduced, show whether the agent is doing its job. The quantitative measures, such as conversion rate, routing accuracy, and rep handoff quality across both systems, show how the business responds. Agree on both sets of criteria up front so the pilot decision follows clear standards.<\/p>\n<h2>How to Defend This to Your VP of Sales<\/h2>\n<p>The internal business case for sales stack consolidation follows a four-part structure that <a href=\"https:\/\/digitalsalespro.net\/articles\/b2b-sales-tech-stack-consolidation-guide-2026\" target=\"_blank\" rel=\"noindex nofollow\">Digital Sales Pro&#8217;s 2026 consolidation guide identifies as the most defensible framing for executive approval<\/a>:<\/p>\n<ol>\n<li><strong>Cost savings first.<\/strong> Calculate total stack cost including integration maintenance and admin time, not just license fees. <a href=\"https:\/\/revenue.io\/blog\/how-many-sales-tools-does-your-team-actually-need\" target=\"_blank\" rel=\"noindex nofollow\">A stack of eight tools at an average of $60 per seat per month totals $480 per seat per month, or $57,600 per year for a 10-person team, a figure most sales leaders miss because each tool is budgeted separately.<\/a><\/li>\n<li><strong>Productivity math.<\/strong> Translate hours reclaimed into dollars using average rep compensation. <a href=\"https:\/\/digitalsalespro.net\/articles\/b2b-sales-tech-stack-consolidation-guide-2026\" target=\"_blank\" rel=\"noindex nofollow\">Eliminating 30 minutes of daily tool-switching and data entry equals 125 hours per rep per year, roughly three additional selling weeks.<\/a><\/li>\n<li><strong>Revenue upside.<\/strong> Tie pipeline velocity improvements to a unified data layer. <a href=\"https:\/\/digitalsalespro.net\/articles\/b2b-sales-tech-stack-consolidation-guide-2026\" target=\"_blank\" rel=\"noindex nofollow\">Organizations with unified tech stacks consistently report 15\u201330% improvements in pipeline velocity because reps have complete context for every interaction.<\/a><\/li>\n<li><strong>AI readiness.<\/strong> Frame consolidation as a prerequisite for deploying AI effectively. AI agents require unified data to function, and tool sprawl remains the single biggest obstacle to effective AI deployment in sales.<\/li>\n<\/ol>\n<h2>The AI-Agent Layer: Coffee as the Consolidation Architecture<\/h2>\n<p>Coffee is the AI-agent layer architecture built specifically for the consolidation problem that RevOps leaders and Heads of Sales face when they evaluate sales stack consolidation alternatives. Legacy CRMs like Salesforce, HubSpot, Dynamics, Attio, Close, and Pipedrive function as passive databases that rely on human data entry, while Coffee deploys an active agent that handles the work itself.<\/p>\n<figure style=\"text-align: center\"><a href=\"https:\/\/www.coffee.ai\/pricing\" target=\"_blank\"><img decoding=\"async\" src=\"https:\/\/cdn.aigrowthmarketer.co\/1763678186019-5cc1a76ac78e.gif\" alt=\"Build people lists automatically with Coffee AI CRM Agent\" style=\"max-height: 500px\" loading=\"lazy\"><\/a><figcaption><em>Build people lists automatically with Coffee AI CRM Agent<\/em><\/figcaption><\/figure>\n<p>The competitive landscape for sales stack consolidation breaks into distinct categories, each with a clear limitation:<\/p>\n<ul>\n<li><strong>Legacy CRMs<\/strong> (Salesforce, HubSpot, Dynamics, Attio, Close, Pipedrive) are passive databases built on pre-AI architectures. They store structured data but struggle with unstructured data like email text or call transcripts, and they rely on reps to maintain data quality.<\/li>\n<li><strong>Modern CRMs<\/strong> (Clarify, Day.ai) are post-ChatGPT tools but lack the integration depth for established teams running Salesforce or HubSpot with quotas, forecasting, required fields, and complex custom workflows.<\/li>\n<li><strong>Standalone visitor ID tools<\/strong> (RB2B, Warmly) surface company-only or undifferentiated people data without closing the loop to outreach.<\/li>\n<li><strong>Standalone prospecting databases<\/strong> (ZoomInfo, Apollo.io) charge separate subscriptions for lead data that lives outside the system executing the outreach.<\/li>\n<li><strong>Dedicated sales engagement tools<\/strong> (Outreach, Salesloft) add another subscription and another silo to the stack.<\/li>\n<\/ul>\n<p>Coffee consolidates these layers into one agent. The specific consolidation wins are:<\/p>\n<ul>\n<li>The Agent handles data entry and enrichment automatically upon connection to Google Workspace or Microsoft 365, replacing tools like Apollo and ZoomInfo for most use cases by augmenting records with job titles, funding data, and LinkedIn profiles via licensed data partners.<\/li>\n<li>The Agent orchestrates meetings with pre-meeting briefings, AI-generated summaries, action items, and follow-up drafts, overlapping with Gong and Fathom without requiring a separate subscription.<\/li>\n<li>The Agent delivers pipeline intelligence including the Pipeline Compare feature, which visualizes week-over-week changes and highlights progressed deals, stalled opportunities, and new additions, replacing manual CSV exports and expensive forecasting add-ons.<\/li>\n<li>The Agent consolidates the stack by performing the jobs of multiple tools: CRM, enrichment, prospecting, recording, outreach sequencing, and forecasting in one system.<\/li>\n<li>Visitor Identification with Suggested Leads surfaces named individuals, not just companies, who visit your website, with Lead Finder and Campaigns natively integrated so the loop from pixel hit to outreach closes inside one agent.<\/li>\n<\/ul>\n<p>Coffee operates in two deployment models. As a Standalone AI-First CRM, the Coffee Agent is the system of record for companies that have outgrown spreadsheets and want a modern alternative without the manual maintenance burden of HubSpot or Pipedrive. As a Companion App for Salesforce and HubSpot, the Coffee Agent handles the intelligence and data-entry layer while the existing CRM retains its role as the system of record. Both models run on a data warehouse architecture that handles structured and unstructured data simultaneously, a capability legacy CRMs cannot match.<\/p>\n<figure style=\"text-align: center\"><a href=\"https:\/\/www.coffee.ai\/pricing\" target=\"_blank\"><img decoding=\"async\" src=\"https:\/\/cdn.aigrowthmarketer.co\/1763678641499-bad085f8165f.gif\" alt=\"Building a company list with Coffee AI\" style=\"max-height: 500px\" loading=\"lazy\"><\/a><figcaption><em>Building a company list with Coffee AI<\/em><\/figcaption><\/figure>\n<p>Coffee is SOC 2 Type 2 and GDPR compliant, does not use customer data to train public models, and uses simple seat-based pricing where the agent&#8217;s unlimited labor is included. Pricing avoids complex metering on LLM usage or agent processes.<\/p>\n<p><a href=\"https:\/\/www.coffee.ai\/pricing\" class=\"solid-button\" target=\"_blank\">Start Your Consolidation Pilot<\/a><\/p>\n<h2>Conclusion: Consolidate the Intelligence Layer First<\/h2>\n<p>Sales stack fragmentation is a sequencing problem rather than a pure vendor selection problem. The three data points cited earlier, including the 79% of activity data that never reaches the CRM, the 22.5% annual data decay, and the 15\u201325 minutes lost per context switch, all point to the same conclusion. Consolidating the intelligence and data-entry layer first solves the underlying data problem before you touch the system of record.<\/p>\n<p>The six consolidation architectures in this guide each address a different layer and fit a different team profile. The AI-agent layer is the only architecture that consolidates all six of those functions without requiring a CRM migration. Coffee is the AI-agent layer architecture for sales stack consolidation alternatives, working either as the standalone system of record or as the agent feeding Salesforce and HubSpot, and serving both SMBs and mid-market teams with reliable data in and reliable data out.<\/p>\n<p><a href=\"https:\/\/www.coffee.ai\/pricing\" class=\"solid-button\" target=\"_blank\">Start Your Consolidation Pilot<\/a><\/p>\n<section data-read-next=\"true\">\n<h2>Read Next<\/h2>\n<ul>\n<li><a href=\"https:\/\/coffee.ai\/articles\/consolidate-sales-tech-stack\" target=\"_blank\">How to Consolidate Your Sales Tech Stack in 7 Steps<\/a><\/li>\n<li><a href=\"https:\/\/coffee.ai\/articles\/sales-stack-consolidation-productivity-benefits\" target=\"_blank\">Sales Stack Consolidation: Key Productivity Benefits<\/a><\/li>\n<li><a href=\"https:\/\/coffee.ai\/articles\/best-sales-tech-stack-2026\" target=\"_blank\">Best Sales Tech Stack for High-Productivity Teams 2026<\/a><\/li>\n<li><a href=\"https:\/\/coffee.ai\/articles\/best-sales-engagement-platforms-2026\" target=\"_blank\">Best Sales Engagement Platforms 2026: Mid-Market Guide<\/a><\/li>\n<li><a href=\"https:\/\/coffee.ai\/articles\/how-to-choose-core-crm\" target=\"_blank\">How To Choose a Core CRM for Sales Stack Consolidation<\/a><\/li>\n<\/ul>\n<\/section>\n","protected":false},"excerpt":{"rendered":"<p>Explore 6 sales stack consolidation alternatives for your team. Coffee consolidates your intelligence layer first. Start simplifying today.<\/p>\n","protected":false},"author":11,"featured_media":9174,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[1],"tags":[],"class_list":["post-9175","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/www.coffee.ai\/articles\/wp-json\/wp\/v2\/posts\/9175","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.coffee.ai\/articles\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.coffee.ai\/articles\/wp-json\/wp\/v2\/types\/post"}],"replies":[{"embeddable":true,"href":"https:\/\/www.coffee.ai\/articles\/wp-json\/wp\/v2\/comments?post=9175"}],"version-history":[{"count":0,"href":"https:\/\/www.coffee.ai\/articles\/wp-json\/wp\/v2\/posts\/9175\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.coffee.ai\/articles\/wp-json\/wp\/v2\/media\/9174"}],"wp:attachment":[{"href":"https:\/\/www.coffee.ai\/articles\/wp-json\/wp\/v2\/media?parent=9175"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.coffee.ai\/articles\/wp-json\/wp\/v2\/categories?post=9175"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.coffee.ai\/articles\/wp-json\/wp\/v2\/tags?post=9175"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}