Gong.io We have found Gong.io to be an invaluable resource. Gong is not purely a forecasting platform, but its intelligence capabilities provide a different perspective than a forecasting technology. Gong is able to analyze information from sales calls and emails to identify trends, rate deal risk based on actual customer interaction, and provide data from your calls and emails to evaluate forecast accuracy. For example, Gong can highlight deals where customer sentiment has shifted negatively, prompting our team to re-evaluate their likelihood to close, offering a layer of qualitative analysis that complements quantitative forecasting data. This has helped us customize our projections beyond just pipeline stages.
Gong fits into how I validate forecasts because it gives me context that numbers alone can't provide. Listening to real conversations--the tone, the hesitation, the objections--helps me understand where deals really stand. It's especially helpful when I'm trying to catch signs of padded optimism or hesitancy that doesn't show up in CRM fields. The volume of data can get overwhelming, though. Without clear tagging and filtering systems in place, the signal gets buried fast. I've found it important to train the team on what to log and how to surface insights so we can keep things focused. There is a clean and modern feel to the user experience. It's easy to navigate, and even folks outside of sales can jump in and find what they need. I don't rely on Gong as a standalone forecasting tool--it works better as a second lens to validate and pressure-test what the CRM is showing. That extra layer of insight helps me make more confident calls.
As founder of UpfrontOps where I've worked with 32 companies over 12 years, I've seen how critical sales forecasting is for scaling operations efficiently. I personally use Gong for sales forecasting across most of my client engagements. The conversation intelligemce features provide unprecedented visibility into what's actually happening in deals rather than just relying on rep optimism. When we implemented Gong with a B2B SaaS client, we uncovered that deals where competitors were mentioned in the first call closed 28% slower - allowing us to adjust our forecasting models accordingly. The biggest drawback with Gong is its pricing structure can be prohibitive for early-stage companies, and you need sufficient call volume to generate meaningful insights. The data analysis capabilities are phenomenal but require someone with analytical skills to extract maximum value. For companies needing a robust alternative, I've had excellent results with Forecastio for clients with complex sales cycles. Their visual pipeline management provides clarity that spreadsheets simply can't match, and their "what-if" scenario modeling helped one manufacturing client properly resource for a major market expansion that would have otherwise been significantly underfunded based on traditional forecasting methods.
Managing Director at Threadgold Consulting
Answered 5 months ago
As someone implementing ERP solutions daily, I've found Salesforce's forecasting capabilities to be particularly strong when integrated with NetSuite for our B2B SaaS clients. The platform's ability to pull data from multiple sources and create custom forecasting models has helped our clients reduce prediction errors by about 25%, though the pricing can be a bit steep for smaller businesses. While the interface isn't always intuitive and requires regular training sessions for our team, the depth of reporting options and reliability of the forecasts make it worth the investment.
At Lusha, we switched to Gong last year and it's been a game-changer for our sales forecasting, especially because it captures actual customer conversations and provides AI-driven insights that help us spot deals at risk. The main drawback is that it can get pretty expensive as your team grows, but the conversation intelligence features have helped us identify winning patterns and coach our reps more effectively.
As CEO of NetSharx Technology Partners, we've helped dozens of mid-market companies transform their tech stacks, and I've seen how critical accurate sales forecasting is for our clients. We primarily recommend Salesforce to our clients due to its comprehensive integration capabilities. When we helped a financial services company migrate from legacy systems, Salesforce's Einstein Analytics provided AI-driven insights that improved forecast accuracy by 30% while reducing their overall tech costs. The main drawback is its complexity - Salesforce requires dedicated resources to maintain and optimize properly. Many of our clients found the learning curve steep without proper implementation support, which is why we provide solution engineers to guide them through setup. For organizations seeking alternatives, we've had success implementing Clari with several retail clients. Its AI-driven approach to pipeline analysis and robust integration with communication platforms like our recommended CCaaS solutions (Five9, Genesys) creates a more holistic view of customer interactions that drive revenue predictions.
As the founder of Cleartail Marketing, I've used Sharpspring's forecasting tools extensively for both our agency and our 90+ B2B clients. The platform's integration with our marketing automation systems provides accurate revenue projections based on lead scoring data. What sets Sharpspring apart is its ability to track the entire customer journey. When we helped a B2B client increase revenue by 278% in 12 months, the forecasting tools were crucial in predicting which leads would convert based on behavior patterns. The main drawback is that it requires consistent data input and regular strategy reviews. We've found weekly updates are necessary to maintain accuracy, especially when dealing with complex B2B sales cycles. For companies wanting a more specialized option from your list, Gong has impressed me with its conversation intelligence capabilities. We've used it with clients to analyze sales calls and identify winning patterns, though its forecasting is more focused on coaching opportunities than pure numerical projections.
As a SaaS founder, I've extensively used Salesforce for our sales forecasting and found its Einstein Analytics capabilities to be game-changing for our revenue predictions. The AI-driven insights have helped us accurately forecast quarterly targets within 95% accuracy, which was a huge improvement from our previous manual processes. While the initial setup was complex and required dedicated training time for our team, the robust customization options and integration capabilities with our tech stack made it worth the investment.
I use Salesforce for sales forecasting at Origin Web Studios because it offers unmatched integration with our existing CRM data. This seamless connection eliminates double entry and provides real-time visibility into our pipeline, which has been crucial for our agency's growth. What sets Salesforce apart from competitors is its customization capabilities. We've tailored the forecasting modules specifically for our website development projects, creating custom fields that track key milestones like design approval and development completion. This gives us more accurate timelines than generic forecasting tools. The main drawback is definitely the learning curve. New team members often struggle with the interface complexity, and we've had to create our own training materials to complement Salesforce's documentation. The platform can feel overwhelming for smaller businesses just starting with forecasting. User experience is comprehensive but not particularly intuitive. The dashboard customization is powerful once you understand it, but requires significant investment to set up properly. That said, the mobile app has improved dramatically in recent years, allowing our team to update forecasts on the go when meeting with clients. I've also briefly tested Gong and found its conversation intelligence features impressive for improving sales techniques, though we ultimately preferred staying within the Salesforce ecosystem for simplicity.
I'm currently using Clari at ShipTheDeal, and I've found its AI-powered forecasting to be incredibly accurate for our e-commerce focused business. After trying various tools including Salesforce, I stuck with Clari because it gives me real-time visibility into deal progress and helps identify at-risk opportunities before they fall through - something that saved us several major deals last quarter. The learning curve is pretty steep and it took my team about two months to fully adapt, but now we couldn't imagine running our sales operations without it.
I discovered Gong's AI-powered analytics when struggling to forecast our SaaS sales accurately, and it's been a game-changer for understanding customer conversations and predicting deal outcomes. The platform's ability to analyze call recordings and identify buying patterns helps us adjust forecasts in real-time, though it took our team about three months to fully utilize all its features. One drawback is that it sometimes misinterprets technical AI-related discussions in our sales calls, but the user interface is incredibly intuitive and the insights are invaluable for our sales process.
I've worked with several sales teams, and Clari has stood out to me. What I love most about Clari is how it goes beyond traditional sales forecasting tools -- it gives real-time visibility into the health of the pipeline, but what makes it unique is its ability to provide actionable insights alongside the numbers. It doesn't just tell you what's likely to close, but also gives you a clear picture of why things might be moving slowly or where risks are emerging. It's been a game-changer in aligning our marketing strategy with the sales team's needs. For example, Clari helped us realize that certain deals were stalling in specific stages, which allowed us to adjust our campaigns to help push those prospects forward. The only downside is that it can be a bit overwhelming for a team not used to forecasting tools of this caliber. The learning curve can be steep, but once your team gets comfortable with the platform, the user experience is smooth and incredibly intuitive. Clari excels in helping teams see the bigger picture, making it easy to align efforts across both sales and marketing.
Sure--I've worked with several of these tools across startups and enterprise-level companies, so I'll share some personal insights that could add some color to your piece. Clari stands out as my go-to for sales forecasting in fast-moving B2B environments. It's incredibly intuitive and gives reps, managers, and execs a clear, real-time view of deal health, pipeline changes, and forecast accuracy. What I like most is how it aligns sales and revenue ops--it's not just forecasting, it's revenue intelligence. One RevOps director I collaborated with said, "Clari is like a nervous system for our pipeline--it tells us what's weak before we feel the pain." The drawback? It's pricey, and setup can take time. For smaller teams, it might feel like using a cannon to kill a fly. Gong isn't a forecasting tool at its core, but when paired with Clari or Salesforce, it becomes incredibly powerful. It gives context to forecasted deals through conversational analytics--so you're not just seeing the number, you're seeing why a deal is or isn't moving. But its forecasting add-ons are still maturing. For teams looking for standalone forecasting, Gong wouldn't be the first pick--but for deal inspection and coaching, it's gold. Salesforce, of course, is the giant in the room. I've used it across multiple orgs, and while its native forecasting tools are flexible, they rely heavily on how well your CRM is customized. If your data hygiene isn't strong, Salesforce can be more frustrating than helpful. The experience varies wildly from team to team, and admin support is key. I've seen teams get lost in overly complex dashboards or give up on forecasting there entirely, using spreadsheets instead.
As someone who's managed over 2,500 WordPress websites and run wpONcall since 2013, I've found Forecastio to be our most valuable sales forecasting tool. Our WordPress maintenance business requires accurate projections for staffing our support team properly while managing cash flow. Forecastio's integration with our WordPress-specific CRM allows us to track renewal patterns for maintenance plans - crucial since we offer 3-month minimum commitments before shifting to month-to-month. Its visual pipeline makes it easy to spot when clients might be considering upgrading or downgrading their plans. The main drawback is Forecastio's limited customization for service-based businesses. I've had to create workarounds for tracking our unique "unlimited support" model where clients can make unlimited requests under 30 minutes each. The user experience is straightforward but not flashy - which actually works well for our technical team. We've seen our forecast accuracy improve by about 22% since implementation, helping us maintain our promised 12-hour (often 1-hour) response times by having the right number of WordPress experts available when demand increases.
As a financial executive with over 10 years in the industry, I've experimented with a range of sales forecasting tools. From Excel spreadsheets in my early days to advanced CRMs, I've seen how the right tool can make or break a quarter. Today, my go-to software for sales forecasting is Salesforce--specifically its Sales Cloud with customizable forecasting dashboards. My favorite thing about Salesforce is that it is very flexible and integrates with everything. It integrates straight into our ERP, marketing systems, and customer success platforms. The AI insights (Einstein Analytics) are very useful, providing not only historical information but also smart predictions. With all that, however, Salesforce is not perfect. It's costly, especially for smaller teams. The installation is also time-consuming, and customization needs in-house talent or a talented consultant. In addition, the user interface is strong but can be overwhelming initially. There is a learning curve, especially for beginners with CRM platforms. But once onboarded, my team says it's easy to use and enables them to move quicker and smarter. Here, speed and clarity are paramount. For me, Salesforce delivers both--and that's why it's still my go-to forecasting tool.
As the founder of Rocket Alumni Solutions (now at $3M+ ARR), I've used Salesforce extensively for our sales forecasting needs. Building software for educational institutions requires accurately predicting lengthy sales cycles that often align with academic calendars and budget approvals. Salesforce's Einstein Analytics gives us predictive insights that helped increase our weekly sales demo close rate to 30%. The custom pipeline stages we created specifically for K-12 and higher education buying processes proved crucial when we expanded from our core touchscreen Wall of Fame product into corporate lobbies. The main drawback is the steep learning curve and cost for smaller teams. I dedicated significant resources to proper implementation when we were still under $1M ARR, which was painful at the time but paid off as we scaled to service educational institutions nationwide. The UX feels dated compared to newer tools like Weflow, but the reliability and depth of reporting more than compensate. When our sales team knows exactly which school budget cycles to target and when, we gain the confidence to make bold product development commitments, like our commitment to build ADA-compliant features that ultimately became a major selling point.
As the founder of Rocket Alumni Solutions, we've scaled to $3M+ ARR using Salesforce for our sales forecasting. Its integration capabilities were crucial when tracking our 80% YoY growth and monitoring our 30% weekly sales demo close rate for our interactive donor and hall of fame displays. I prefer Salesforce because it allows us to segment forecasting by institution type (schools vs. corporate lobbies) which was vital when we expanded beyond K-12 institutions. The customizable pipeline visually represents our unique sales cycle where deals typically close after in-person demos of our touchscreen software. The main drawback is the steep learning curve and implementation cost. For a startup, the initial setup required significant resources that could have been allocated elsewhere. We had to customize heavily to track our unique metrics around donor engagement and retention. The user experience is robust but complex. What I appreciate most is the mobile functionality that lets me update forecasts right after campus meetings with athletic directors or advancement officers. This real-time updating has been essential for our distributed sales team who are constantly visiting potential client schools across the country.
I've been using Salesforce for our SEO agency, and what really sold me was how it syncs perfectly with our SEO analytics tools to forecast traffic patterns and conversion rates. Last year, we integrated it with our client reporting dashboard, which helped us predict seasonal SEO demand spikes with about 85% accuracy. While the learning curve was steep and the cost is definitely on the higher side, the customizable dashboards and robust API integrations make it worth the investment for our growing team.
We've been using Salesforce paired with Clari to manage and refine our sales forecasting. This combo gives us visibility, pattern recognition, and practical alignment between sales and operations. Salesforce is our core CRM and it's been reliable for structuring our pipeline but where it really comes alive is when we integrate Clari on top of it. That's when we started to get actual forecasting rather than just reporting. Clari helped us identify which deals were slipping which reps were overestimating and where the gaps were between forecast and actuals. I remember one quarter where we were counting on a few big deals to hit. Clari flagged two of them as "at-risk" based on lack of recent activity. Our team hadn't seen the warning signs yet. We shifted our attention to mid-sized deals we were neglecting and closed several of them to hit target. Without that heads-up, we would've missed the mark. The downside? Clari isn't cheap, for a mid-size company like ours, we debated the cost but once we saw that it helped us recover roughly $120,000 in one quarter by shifting focus in time, the decision was easier. User experience is solid once you're in, but there's a learning curve. My sales leads adapted quickly. For our factory team, it took more time to grasp how sales forecasts influence operations. Now we review our forecast weekly across departments. It's made communication cleaner, and fewer surprises come up. I've looked into tools like Forecastio and Avercast before, especially for demand planning, but I found them more tailored toward high-volume retail or tech businesses. For us, where every gym install or international shipment is complex and customized, Salesforce + Clari gives us the flexibility we need.
As CEO of Rocket Alumni Solutions scaling to $3M+ ARR, we use Salesforce with HubSpot integration for sales forecasting. Our decision stemmed from needing enterprise-grade reliability while managing 600+ school and university clients with varying sales cycles. What separates Salesforce is its customization capabilities - we built custom objects to track touchscreen hardware deployment timelines alongside software subscriptions, which dramatically improved our forecast accuracy by 30%. The Einstein Analytics features help us identify which recognition display demos convert at higher rates (currently 30% weekly close rate). The main drawback is the steep learning curve for new sales team members. We implemented a mentor system pairing veterans with newcomers to overcome this, but still budget 2-3 weeks before new reps can effectively use the platform. For schools considering competing products, I'd recommend looking at IBM Planning Analytics if you need multi-department forecasting capabilities. When exploring expansion into corporate recognition displays beyond our core K-12 market, we briefly tested it and found its scenario modeling funvtionality particularly strong for projecting different market segment performances.