Weflow

KORE's Salesforce data didn't reflect reality. ❌ Activities missing ❌ Deal values inflated by reps ❌ No visibility into what was actually happening Without a trusted data layer, forecasts and pipeline values couldn't be validated. They started looking for a solution. Came across Gong, but the pricing didn’t justify its value So they chose Weflow. Not just because it cost less. But because it solved a bigger problem: 👉 A unified data foundation in Salesforce 👉 Deal gaps and warnings flagged in real time 👉 Forecasts based on real data, not optimism Read the case study to learn more.

IDnow uses Weflow to automatically capture all emails, contacts, and meetings directly into Salesforce. The result? Reliable reporting that leadership actually trusts. Don’t take our word for it - see it in action with your own data. Book a quick demo and start your 14-day free trial.

Most B2B RevOps teams struggle with Salesforce data hygiene. Argus Media was no different. Before automating it with AI, they faced 3 core issues: 1️⃣ Key Salesforce fields (like ‘next steps’) were often empty 2️⃣ Customer emails & meetings didn’t make it into the CRM 3️⃣ Leadership lacked visibility into the pipeline and forecast They joined 200+ RevOps teams already using Weflow to overcome these challenges. Read the case study to learn more.

Blacklane tested several solutions to automate their activity data capture. They faced the same problems you likely have: incomplete customer history, missing email threads and more. So they switched to Weflow. Now, every email, contact, and meeting is automatically captured in Salesforce. No gaps. No manual admin work. Don’t take our word for it - see it in action. Book a quick demo and start your 14-day free trial.

Last week, the CRO of a $42M ARR SaaS turned to us. They missed their Q1 forecast by 28%. The board wasn't happy. Here's the playbook we used to fix it. Context: I talk to dozens of sales leaders every month. This CRO was not an exception: - Inaccurate forecasts due to poor visibility - Poor visibility due to missing CRM data - No clear process & accountability Here's a proven playbook that has helped 200+ B2B SaaS CROs & RevOps teams forecast accurately (that's exactly what we built Weflow for: https://lnkd.in/eK7rhMaY): 𝗙𝗶𝘅 𝟭: 𝗨𝘀𝗲 𝗔𝗜 𝘁𝗼 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗲 𝗦𝗮𝗹𝗲𝘀𝗳𝗼𝗿𝗰𝗲 𝗵𝘆𝗴𝗶𝗲𝗻𝗲 Data quality is the foundation of effective deal reviews and visibility into pipeline & forecast health. This has two components - 1) AI activity data capture: Why it matters: - Emails/meetings not logged = unclear deal velocity - No engagement = high risk of deal slippage - No activity data = forecasts based on gut feel E.g. - Last activity date - Next meeting date - Email reply rate .. Situation: The CRO & RevOps team faced 3 issues: - Reps forgot to log activities - Auto-logging failed (poor opp & contact role mapping) - Most opps lacked contact intelligence (who’s involved, decision-maker, multi-threading) No activity/contact insights = no visibility. Solution: Use AI tools that auto-capture emails & meetings and map contacts accurately. Ideally, it should have an Outlook Add-In/Google Extension to improve opp mapping (e.g. Weflow does this). 𝟮) AI CRM updates: Why it matters: - Often missing key fields (e.g. MEDDIC) - Bad CRM data = poor deal reviews & forecasts Situation: - Reps hated manually updating Salesforce. - 76% of their MEDDIC fields were not populated. - Managers lacked deal visibility. Solution: With AI, there's no reason why reps should be doing this manually in 2026. Use AI enabled conversation intelligence tools that extract and update MEDDIC fields in SFDC from call transcripts. 𝗙𝗶𝘅 𝟮: 𝗨𝘀𝗲 𝗔𝗜 𝘁𝗼 𝗳𝗹𝗮𝗴 𝗱𝗲𝗮𝗹 𝗮𝗻𝗱 𝗳𝗼𝗿𝗲𝗰𝗮𝘀𝘁 𝗿𝗶𝘀𝗸𝘀 𝗲𝗮𝗿𝗹𝘆 Why it matters: To improve deal reviews & forecasts, managers need full visibility into deal and pipeline health: - Push count - AI warnings - Multi-threading & velocity .. Solution: Configure insights in Salesforce or use Revenue AI / forecasting tools that flag deals that are stalling, single threaded or have no next step. 𝗙𝗶𝘅 𝟯: 𝗖𝗼𝗺𝗯𝗶𝗻𝗲 𝗳𝗼𝗿𝗲𝗰𝗮𝘀𝘁 𝗺𝗲𝘁𝗵𝗼𝗱𝗼𝗹𝗼𝗴𝗶𝗲𝘀 𝗮𝗻𝗱 𝗺𝗼𝗱𝗲𝗹𝘀 Situation: They ... - Only forecasted new logos (ignoring expansions/renewals) - Used weighted forecasts + spreadsheets (highly inaccurate) Solution: - Opp record types for expansion/renewals - AI creates renewal opps upon closed-won - Combine models like bottom-up/roll-up, (dynamically) weighted pipeline, AI predictions I didn't touch upon revenue cadence/process due to character limits (but we helped fix this too). What do you think drives forecast accuracy?

Missed the forecast again? Now the spotlight is on you. Leadership stops trusting you. Every number gets a second look. And the pressure keeps rising. But without full pipeline visibility, it's no surprise the forecast went wrong. You can't see which deals went quiet. Whether the right stakeholders are involved. Or which close dates are slipping. It doesn't have to be that way. Weflow gives you full pipeline visibility: 👉 50+ AI deal signals and deal health scoring 👉 Configurable warnings for deals at risk 👉 Automated forecast roll-ups across your team 👉 AI forecast prediction So your forecast stops being a guess. And becomes a number you can defend.