Nektar & Gong Integration: Bring Every Sales Conversation Into Your Complete Customer Story Product Update 5 min August 10, 2026 We’re excited to announce that Nektar now integrates with Gong, making it easier for revenue teams to unify conversation intelligence with every other customer interaction. The integration automatically captures Gong call data, including participant attendance, call duration, and meeting transcripts, and combines it with email, calendar, meeting, and CRM activity already flowing through Nektar. The result is a complete customer engagement timeline that gives RevOps, Sales, Marketing, Customer Success, and AI agents far more context than conversation data alone. Whether you’re trying to improve CRM completeness, understand buying committee engagement, measure campaign influence, or power AI with better customer data, the Nektar + Gong integration brings another critical source of customer intelligence into your GTM data foundation. Get our latest insights into your inbox Why integrate Gong with Nektar? Sales conversations contain some of the most valuable information about a deal. They reveal customer pain points, objections, buying signals, and next steps. But that information often stays inside Gong while the rest of the customer journey lives elsewhere. With the Nektar integration, Gong conversation data is automatically captured and added to the same engagement layer as every other customer interaction. For every synchronized Gong meeting, Nektar captures: The participants who actually attended the meeting. The duration of the conversation. The complete meeting transcript. Attendance information reflects who joined the call, not just who accepted the calendar invitation, giving revenue teams a much more accurate view of stakeholder participation throughout the buying process. This works across Gong-recorded meetings on Google Meet, Zoom, and Microsoft Teams, bringing conversation intelligence together regardless of which meeting platform your teams use. View full Feature Comparison Nektar vs Gong: What’s the difference? Conversation intelligence is only one piece of customer intelligence. Compare both platforms side by side to understand what each one captures, where they overlap, and where they don’t. Turn conversations into structured business insights Capturing conversation transcripts is only the beginning. The real value comes from turning those conversations into structured data that revenue teams can act on. With Nektar, organizations can automatically extract insights from Gong transcripts based on their own business processes and map those insights into Salesforce. Instead of manually reviewing calls or relying on ad hoc notes, teams can standardize the information they care about and make it available across their CRM. For example, businesses can capture and populate fields such as: Competitors mentioned during sales conversations Product features discussed Customer objections or risks Next steps and agreed action items Budget, timeline, or implementation signals Any custom insight specific to their sales process Because these insights are written directly into Salesforce, RevOps teams can build dashboards, reports, workflows, and automations using conversation data that would otherwise remain locked inside transcripts. Instead of treating conversations as unstructured text, Nektar turns them into structured, reportable CRM data that can be analyzed alongside every other customer interaction. What can you build with Gong Data? By combining Gong conversation data with engagement across email, calendars, meetings, and CRM activity, Nektar gives revenue teams a much more complete understanding of customer relationships. Campaign-to-conversation attribution Marketing teams can finally connect demand generation efforts with sales conversations. Instead of manually matching campaign reports against Gong recordings, teams can see which campaigns, webinars, events, or content pieces ultimately resulted in customer conversations and pipeline progression. That creates much clearer visibility into how marketing engagement influences revenue beyond the initial lead conversion. Cross-channel engagement scoring Nektar combines Gong participation data with email responsiveness, meeting attendance, and other customer interactions to calculate engagement scores for both contacts and accounts. These scores reflect how customers engage across every touchpoint instead of relying on a single communication channel, making it easier to identify highly engaged buyers, stalled opportunities, and disengaging stakeholders. Buying committee visibility Modern B2B purchases involve multiple decision makers, influencers, and champions. Because Nektar combines Gong attendance data with CRM relationships and every other customer interaction, teams can understand how deeply an opportunity is multithreaded, which stakeholders remain engaged, and where additional relationship building is needed before a deal reaches a critical stage. Build AI on complete customer context As organizations adopt AI across sales, RevOps, and Customer Success, customer context becomes increasingly important. Conversation transcripts are valuable, but they don’t tell AI what happened before the meeting or how customer engagement changed afterward. By bringing Gong conversation data together with every other customer interaction, Nektar creates a richer customer intelligence layer that AI agents can use for forecasting, deal inspection, account planning, buying group analysis, customer health monitoring, and revenue intelligence. Instead of asking AI to reason over fragmented systems, organizations can provide a complete view of customer engagement across the entire buying journey. Connect Gong in minutes Availability Note: The Gong connector will be available in the Nektar Connectors UI in the upcoming release. Until then, if you’d like to enable the Gong integration, please reach out to your Customer Success Manager, who will help you get started. The Gong integration uses OAuth authentication, making setup both secure and straightforward. Getting started only takes a few steps: Open the Connectors page in the Nektar dashboard. Select the Gong integration and click Connect. Authenticate with Gong and approve the required permissions. Choose which Gong users should synchronize. Start automatically capturing conversation data. Administrators can independently control call synchronization and transcript synchronization for each user, providing flexibility over which information is ingested while maintaining centralized governance. Once connected, Nektar continuously synchronizes Gong data without requiring any additional work from sales representatives. Now available on the Gong Marketplace To make deployment even easier, the Nektar integration is now live on the Gong Marketplace under the AI Platform category. Organizations already using Gong can discover Nektar directly through the Marketplace, authorize the integration using OAuth, and begin enriching their customer engagement data in just a few minutes. Whether your goal is improving CRM completeness, understanding buying committee engagement, measuring campaign influence,

Top 7 Data Cleansing Tools Blog CRM 10 min Updated: July 30, 2026 What Is Data Cleansing? Data fuels every insight and decision a modern business makes, but raw data is rarely clean on arrival. It’s riddled with inconsistencies, errors, and duplicates, “dirty data” that leads directly to inaccurate analysis, flawed decisions, and wasted resources if it goes unaddressed. The scale of the problem is well documented. Gartner has found that only 3% of data meets basic quality standards, and separately estimates the average cost of poor data quality at $12.9 million per organization annually. Data cleansing, also called data scrubbing, is the process of identifying and correcting or removing corrupt, inaccurate, or irrelevant data from a dataset. It’s essential for maintaining data integrity and making sure decisions get made on numbers that actually reflect reality. Get our latest insights into your inbox Why Your Company Needs It Picture your best rep enthusiastically chasing a lead, only to find the phone number is wrong and the email bounced. That’s dirty data in action, and reps run into it constantly. Inaccurate, missing, or duplicated CRM information creates unnecessary friction for exactly the people trying to close deals, the equivalent of taking wrong turns across town: you might eventually arrive, but only after burning hours you didn’t need to. Dirty data quietly costs a business in a few specific, compounding ways: Wasted time and resources. Reps spend hours chasing cold leads, fixing mistakes, or manually verifying details that should have been correct in the first place, time that should have gone toward actually selling. Missed opportunities. Inaccurate data creates a real blind spot: targeted outreach fails to reach existing customers, and prospecting misses new ones. A single bounced email address can be the difference between closing a big account and never hearing back. Poor decision-making. Dirty data skews reports and metrics, distorting the picture leadership is actually working from and leading to decisions that look reasonable on the dashboard and wrong in practice. Strained customer relationships. Irrelevant outreach or contacting the wrong person at an account reads as carelessness to the buyer, damaging trust and making the company look sloppy at exactly the moment it’s trying to build credibility. Proper data cleansing turns chaotic, unreliable data into a single, trustworthy source of truth, and the tools below each take a different approach to getting there. Top 7 Data Cleansing Tools for 2026 Nektar, AI-powered CRM data hygiene, built to prevent dirty data at the source OpenRefine, free, open-source cleansing and transformation Tibco Clarity, enterprise-grade cloud data cleansing and management WinPure Clean & Match, specialist matching and deduplication Integrate.io, cloud ETL/ELT with built-in cleansing Melissa Clean Suite, address hygiene and verification Mammoth.io, no-code data transformation and cleaning Overview of the 7 Best Data Cleansing Tools 1.Nektar Salesforce data can quietly turn into a mess that undermines the reliability of every report built on top of it. Nektar addresses this differently than the other six tools on this list: instead of cleansing data after it’s already dirty, it automatically captures contact and activity data directly from email, calendar, and meetings, and writes it into Salesforce correctly structured from the start, preventing a large share of dirty data from ever entering the system in the first place. Here’s how Nektar solves the problem specifically: Unmatched sync accuracy. Nektar doesn’t just import data at a basic level. It analyzes records using AI to establish links between accounts and opportunities, and assigns confidence scores to each match, cutting out redundant entries and giving reps a single, reliable view of what’s actually happening on an account. Time Travel for historical context. Nektar identifies past interactions, contacts, emails, meetings, tied to a given domain and links them into newly created opportunities, even ones that predate the opportunity’s own creation. This retroactive correction gives reps and managers real historical context on a live deal instead of a record that only starts the day someone remembered to create it. Effortless reporting. High-quality reporting depends on clean data underneath it. Nektar makes this straightforward by automatically syncing contacts, emails, and meetings directly into standard Salesforce objects, so a report reflects what actually happened rather than what got manually logged. Self-healing records. Nektar continuously learns and adjusts, updating CRM records as new information arrives and incorporating manual changes users make along the way, so the data stays accurate on an ongoing basis rather than degrading again right after a cleanup project ends. Smart contact creation. New contacts get created automatically and matched to existing accounts by domain, removing a repetitive manual task and keeping account records properly connected instead of fragmented across near-duplicate entries. Parm UppalCRO, Chainguard Nektar was the first investment I made in my new role because we needed telemetry we could trust. Unlike traditional data cleansing, which requires manual work or a separate third-party tool layered on top of a CRM, Nektar is an AI-powered solution that integrates directly with Salesforce and handles most of this automatically. It keeps learning and adjusting, so data stays clean and accurate on an ongoing basis, freeing reps from the grind of manual data entry so they can focus on actually closing deals. 2. OpenRefine OpenRefine (formerly Google Refine) is a well-established open-source tool for cleaning and transforming messy data. It maintains data in a consistent format, sorts it according to your own rules, imports from web sources, and applies clustering algorithms to solve genuinely complex data-cleaning problems. Where it stands out: Free and open source. Costs nothing to install and can be extensively customized. Broad functionality. Handles a wide range of transformation, cleansing, and parsing tasks across diverse data sources. A relational approach, stronger than a simple flat spreadsheet for handling connected data. Local, on-machine security, rather than uploading sensitive records to a cloud platform. The tradeoff: OpenRefine’s interface is genuinely trickier than most commercial tools on this list, and it takes real technical comfort to use it well. 3. Informatica Data Quality Informatica Data Quality is a large-scale, cloud-based data cleansing

Nektar vs. Clari vs. Gong vs. Backstory (People.ai) vs. EAC Product 15 min Updated: July 29, 2026 Automated data capture stopped being a nice-to-have for revenue teams years ago. In 2026, it’s become something closer to infrastructure: the layer that determines whether an AI agent acting on your CRM is working from a complete picture or a partial one. This comparison covers five platforms that all promise some version of automated capture, AI-driven insight, and cleaner CRM data, Nektar, Clari, Gong, Backstory (formerly People.ai), and Salesforce’s own Einstein Activity Capture, and where each one actually delivers versus where the marketing outruns the product. Two of these five have changed meaningfully since this comparison was last written, and getting that history right matters if you’re evaluating them today: People.ai rebranded to Backstory in April 2026, and Clari merged with Salesloft in December 2025. Both are covered accurately below, not under their old, standalone identities. Get our latest insights into your inbox Nektar Nektar was founded in 2020 with a vision to help GTM teams close revenue leaks with a purpose-built AI data foundation that unifies accurate, clean, timely revenue data automatically, at scale. That thesis has sharpened since: Nektar’s current positioning is making Salesforce data trustworthy enough for both reps and AI agents to act on directly, not just clean enough for a human to read. Claim to Fame Nektar’s Data Foundation automatically syncs contacts, emails, and calendar meetings from sales communication into Salesforce, for ongoing activity and historical GTM activity alike, with zero rep effort required.  Time Travel goes further, retroactively correcting historical records as new context arrives, something none of the other four platforms in this comparison do. Daisy AI sits on top, surfacing 39 signals across deal risk, buyer engagement, and rep performance directly on the Salesforce Opportunity tab. It supports every customer-facing team, business development, sales, customer success, and account management, which is why revenue operations leaders specifically choose Nektar for a genuine 360-degree view of the customer, not just a sales-only slice of it. Pros: Captures historical and ongoing contacts and GTM activity to deliver genuinely complete CRM data, not a partial sync Automatically presents the buying committee in every deal by enriching contacts with job titles and buyer roles (influencer, decision maker, economic buyer) Automatically links captured contacts to relevant open opportunities as Opportunity Contact Roles, not just Account-level records Classifies activity by sales or CS process automatically, surfacing exactly how sellers and CSMs are actually spending their time Captures calendar events including recurring events and any updates made to them (participant or schedule changes) Always-on reporting delivered directly to Slack, email, or MS Teams, the power of a dashboard without requiring anyone to open one Time Travel™ continuously maintains CRM data, updating and correcting records as new context arrives rather than leaving them static Works for every customer-facing team, not sales alone, including partnership, channel, and alliance teams Vendor-neutral by design, sits alongside Gong, Clari, or Salesloft rather than replacing them Cons: Best suited for companies with 10+ sellers; smaller teams may not need the full depth of the platform As a more specialized data-foundation layer rather than an all-in-one suite, teams wanting conversation intelligence or forecasting UI natively often pair Nektar with a complementary tool rather than expecting Nektar to do everything Clari (Now Clari + Salesloft) Founded in 2012, Clari built its reputation on AI-driven forecasting and predictive analytics for sales teams. In December 2025, Clari merged with Salesloft, forming a combined revenue-orchestration company under CEO Steve Cox, adding Salesloft’s sales-engagement layer (and Clari’s earlier Groove acquisition) to Clari’s forecasting core. If you’re evaluating “Clari” today, you’re really evaluating this combined platform, not the standalone forecasting tool it used to be. Claim to Fame Clari is still best known and most appreciated for its forecasting capabilities specifically, funnel views, pipeline inspection, and forecast rollups that sales leadership teams lean on heavily. Post-merger, it’s positioning itself as a full revenue-orchestration platform spanning forecasting, engagement, and conversation intelligence in one place, which is a meaningfully bigger promise than the pre-merger product made. Pros: Clean visuals and UI, widely regarded as one of the more polished interfaces in this category Customizable dashboards and a genuinely useful “funnel view” of the pipeline Strong visibility into current and projected pipeline for forecast rollups The Salesloft merger adds sales engagement and cadence automation natively, reducing the need for a separate tool for that function Conversation intelligence (via the earlier Chorus.ai and Wingman lineage) now bundled in, easier to consolidate vendors if you want one platform for forecasting, engagement, and calls Cons: Several contacts still aren’t reliably captured in Salesforce; contact-level completeness has been a longstanding weak point independent of the merger Syncing activity into Salesforce Opportunities isn’t always accurate Salesforce sync issues persist as a recurring theme in user feedback User adoption remains a real risk, and requires ongoing enablement investment to sustain The merger itself introduces real integration risk in the near term; analysts including Forrester have flagged genuine product overlap between the combined pieces that’s still being worked through as of mid-2026, worth a direct conversation with the vendor about current integration maturity before committing Read Detailed Comparison Comparing Nektar & Clari? Gong Founded in 2015, Gong built the conversation-intelligence category, using AI to analyze customer calls and meetings and surface coaching and deal-risk insight from what was actually said. It remains a large, well-resourced, independent company (no merger or rebrand to report here) and has continued investing in AI-native forecasting and coaching since this comparison was last written. Claim to Fame Gong is still best known for helping sales leaders coach reps and ramp new hires faster through conversation intelligence, accuracy and depth of insight from actual call and meeting content remain genuinely best-in-class. What started as a sales-team tool has expanded into real usage among customer success and SDR/BDR teams as well, given its focus on conversation-based engagement broadly. Pros: Ramps new sellers faster and coaches existing reps more specifically, grounded in what

Backstory (formerly People.ai) Alternatives: 10 Options for 2026 Product 11 min Updated: July 20, 2026 People.ai rebranded to Backstory in April 2026, repositioning itself from an activity-capture platform into what it now calls a “Revenue Answers Platform” which is a conversational AI layer that reasons over captured activity data to answer natural-language questions about deal and account health. Same underlying company, same core capture technology, a meaningfully different pitch. That rebrand is also a useful marker for something bigger that’s happened across this entire category since the original version of this list. Every tool built in the last decade for “capture activity, show a dashboard” is now being measured against a different bar: can it feed an AI agent that acts on that data directly, not just a human reading a report. That’s the lens this update applies to all ten entries below. Get our latest insights into your inbox What Is Backstory (formerly People.ai)? Backstory automatically captures sales activity like emails, meetings, and calls, and structures it against CRM records. What’s new since the April 2026 rebrand is a conversational interface layered on top: instead of navigating dashboards, users can ask natural-language questions about deal or account health and get an AI-generated answer reasoning over the captured activity. Worth knowing before you evaluate it: a conversational layer is only as reliable as the data it’s reasoning over. Read detailed feature comparison Comparing Nektar & Backstory (People.ai)? Top Backstory / People.ai Alternatives for 2026 1. Nektar Nektar GTM telemetry platform that automatically captures every customer interaction and delivers clean data to your CRM, data warehouse, and AI applications, with zero manual entry or adoption friction. Unlike tools that lock your data in proprietary interfaces, Nektar acts as revenue signals infrastructure: capturing emails, meetings, calls, and Slack, then piping structured intelligence into Salesforce, Snowflake, Claude, and your entire stack. Data Foundation automatically captures every email, meeting, call, and calendar event and writes it natively into Salesforce, HubSpot, or Dynamics — zero rep effort, live in under two weeks. Time Travel retroactively corrects historical records as new context arrives, closing a gap no point-in-time capture tool (including Backstory) can touch. Daisy AI then surfaces 39 signals across categories like buyer visibility, deal risk, and rep performance directly on the Salesforce Opportunity tab. Key features: Zero-rep-effort capture across email, calendar, meetings, and calls Time Travel retroactive correction: up to 12 months of historical backfill Daisy AI signal library across buyer visibility, deal risk, and forecast-relevant flags Vendor-neutral as it sits alongside your existing sales stack rather than replacing it Best for: Salesforce-first enterprise teams that need CRM data reliable enough for AI agents to act on directly, not just a cleaner dashboard. 2. SetSail (now part of ZoomInfo) SetSail was acquired by ZoomInfo in 2024 and now operates within ZoomInfo’s broader platform rather than as an independent company. It still functions as an AI-powered sales data layer capturing activity across email, calendar, and call transcripts and surfacing the specific rep behaviors that correlate with winning deals, plus incentive mechanics to reinforce them. Key features: automated activity capture across email, calendar, and calls; behavioral pattern analysis tied to deal outcomes; MEDDPICC-style meeting-prep summaries; incentive and gamification layer for reinforcing winning behaviors. Best for: Teams already invested in the ZoomInfo ecosystem wanting behavioral analytics layered on top of activity capture. 3. Einstein Activity Capture (EAC) EAC remains Salesforce’s native tool for syncing email and calendar activity into Salesforce records. It’s a reasonable baseline for teams that want activity visibility without adding a third-party vendor, though it lacks the AI-driven signal layer — deal risk scoring, buyer engagement analysis — that dedicated revenue intelligence tools build on top of similar capture data. Key features: captures email and calendar events from Microsoft or Google accounts, logs activity to the Salesforce timeline, native to Salesforce with no separate vendor relationship required. Best for: Teams wanting basic activity capture natively inside Salesforce without additional AI features or vendor cost. 4. MatchMyEmail MatchMyEmail automates email and calendar logging into Salesforce, working with any email client or host rather than requiring a specific inbox provider. It’s a narrower, lighter-weight tool than most others on this list — no AI signal layer, just reliable, automated capture. Key features: automatic email and calendar capture, permanent storage of historical communication data, compatible with any email client. Best for: Teams wanting straightforward, dependable activity logging without a broader intelligence platform attached. 5. Revenue Grid Revenue Grid combines activity capture with guided-selling and forecasting features — 360-degree pipeline visibility, forecast-to-actual comparison, and revenue signals aimed at improving process consistency across a sales team. Key features: 360-degree pipeline visibility, forecast accuracy tracking, guided-selling signals embedded in Salesforce. Best for: Teams wanting activity capture bundled with broader guided-selling and forecasting tools in one product. 6. Aviso AI Aviso’s forecasting engine is now paired with MIKI, a conversational orchestrator that can query pipeline data and trigger CRM updates directly, alongside a library of 50+ pre-built revenue agents and a no-code studio for building custom agentic workflows. Key features: MIKI conversational AI orchestrator, predictive forecasting, 50+ pre-built revenue agents, no-code agent workflow builder. Best for: Teams wanting AI agents built directly into forecasting and pipeline execution, not just activity capture with a chat interface layered on top. 7. Collective[i] Collective[i] has repositioned itself around what it now calls “applications and agents” for sales forecasting and CRM optimization, explicitly framing its mission around helping organizations “operate with the speed and precision required to compete in an AI-first world.” Underneath the updated positioning, its core capability remains automated activity capture combined with AI-driven forecasting and opportunity scoring. Key features: AI-driven forecasting and opportunity-win probability, automated activity and contact capture into CRM, professional-network intelligence for surfacing warm relationship paths. Best for: Teams wanting forecasting and relationship-network intelligence combined in one platform. 8. LinkPoint360 LinkPoint360 focuses specifically on email integration for Salesforce and Microsoft Dynamics — one-click email logging, custom object and field detection, and client-side deployment for teams with stricter data-residency requirements.