AI-powered proposal automation helps sales teams respond to opportunities faster by automating proposal creation, approvals, and negotiations, reducing delays and accelerating deal closures.
You might be losing as many as half of your deals to vendors that respond first, which makes getting proposals out the door quickly a priority. But you can rarely just draft something in a single sitting and send it off. Even a high-growth sales team selling simple products need to get at least an approval or two before a proposal goes out, as well as making sure terms are correct. As the tasks involved in preparing proposals pile up, that initial response to a prospect who’s ready to buy becomes slower and slower.
Proposal automation, especially when powered by AI, can drastically reduce the time needed to go from an initial request for proposal to a closed deal.
The right tool goes beyond just producing templates for sales reps to fill out. It automates processes across the three main time sinks in your proposal process: creation, approval, and negotiation.
Here’s how.
According to Loopio’s RFP Response Trends & Benchmarks Report, sales teams with the highest win rates spend an average of 33 hours writing each RFP response. But when getting a proposal to a prospect first can have such a massive impact on your overall win rate, you’re stuck between two competing goals. Proposals need to be thorough, well-researched, and customized to each prospect’s needs. Proposals also need to go out at the optimal time to reach prospects when they’re primed to make a decision. It feels like having a rigorous proposal process gets in the way of winning deals.
Sales isn’t just about moving quickly; it’s about knowing when speed makes a difference. Rushing through a call with a prospect, for example, is a great way to tank a deal. But responding to a lead in five minutes or less means you’re 100x more likely to connect with a prospect.
The same is true with proposals. When you strike that perfect balance between sending a proposal quickly and putting in the time to write a stellar proposal, you’ll see the difference in your win rates.
Proposals often get delayed at three important stages: initial creation, approval, and negotiation. At the creation stage, the cost of a sub-optimal process is a bottleneck, where overwhelmed reps struggle to keep up with your pipeline. That means even no-brainer deals get lost in the shuffle and prospects disappear. Delays in the approval can, at best, lead to lost deals. At worst, teams might start side-stepping essential approval steps to secure deals faster. At the negotiation stage, quick proposals are essential so sales and prospects can align on what’s important and move forward.
Proposal automation isn’t about completely taking your sales team out of the process. It’s about finding the right balance between eliminating manual work while maintaining total control over the final output. Proposal automation might automatically generate templates for each prospect, streamline your approval process, or support your teams with AI agents that take on complete workflows.. It’s not a magic button you press at the end of a call that takes on every aspect of generating and sending a proposal.
Since the time you spend on proposals translates directly to increased win rates, that’s not something you would want, anyway.
Few sales teams truly start every proposal from scratch. They use templates, copy terms from past proposals, and reference CRM data. While many sales tools can streamline this process by providing pre-built templates or generating small bits of text, true proposal automation goes beyond this. It learns more about your brand over time, meaning every proposal is on-brand from the start. It guides you through the proposal process with a chat bot that answers questions or shares best practices. It becomes the connective tissue between all your apps, so it always has the data it needs to create better proposals.
Proposal automation typically relies on three types of technology:
To accelerate your proposal process in a meaningful way, proposal automation needs to impact proposal creation, review cycles, and negotiation times. Here’s how.
When you look at proposal creation holistically, you’ll find a number of tasks where your sales team can potentially get caught up, creating productivity drag. Tasks like:
Then there’s all the administrative work that comes with proposals, from updating old templates to maintaining relevant information for future proposals.
Where other tools might only offer templates to start from, proposal automation software can play a role in all of these tasks, from automatically generating executive summaries to using data from past proposals to optimizing the way you present pricing.
Your approval cycle is about more than just checking off boxes before you send a proposal off. It’s about ensuring each stakeholder has the opportunity to review what they need to see without overwhelming them with everything else. The same is true on the prospect side, when your proposal is received and their stakeholders need to review it. This stage can potentially take the longest, depending on the amount of back-and-forth required. These approvals depend on having the right information on hand, and having to search things up manually can slow these cycles down. Automation proposal software shouldn’t just generate proposals; it should also streamline approvals. Chat bots can answer questions ahead of necessary approvals, while AI agents can independently seek out information stakeholders need to review a proposal.
The goal isn’t to replace human approval cycles, but to automate what can be automated and facilitate what can’t.
Free Pro provides IT, telecom, cloud, and cybersecurity services to private companies and public institutions, which involves producing accurate, customized proposals aligned with specific needs outlined through sometimes lengthy pre-sales conversations. The information needed to build these proposals was scattered across Word documents, personal libraries, and other systems, meaning there was no shared foundation for any of them.
By turning to Cobl, Free Pro started generating structured, customized proposals with AI-assisted workflows, based on centralized, validated content. Instead of contributing to clutter and overwhelm, every previous document became a data point for future proposals.
The result? 350% ROI and an RFP response time that went from several days to just two hours.
Check out the full story here.
Dedicated proposal automation tools integrate directly with your CRM. That doesn’t just give them access to a treasure trove of data that can be mined for building better proposals; it also allows you to automate crucial actions. Generating instant proposals from opportunities means your sales team can get a headstart on potential deals, reviewing and validating proposals as they move through other stages rather than dedicating full workdays to creating them.
Agentic AI goes beyond just generating text. Think of every AI agent like a new team member, able to take on tasks and complete them autonomously, making decisions on the fly as needed. AI agents can collect the information you need, outline a proposal, and generate your proposal content simultaneously.. Agentic AI is a force multiplier that saves you a ton of time and effort at every stage of the proposal process.
For all their faults, platforms like Google Docs have one advantage when drafting proposals: real-time collaboration. Long email chains with attachments slow things down unnecessarily, and proposal automation tools find the middle ground between the two. They don’t just generate proposals; they give teams a place to collaborate on them alongside AI agents that streamline their work.
Up to 70% of marketing content goes unused, and the ratio in your sales team is likely no different. The problem isn’t a lack of content, it’s in finding the content you need when you need it. Proposal automation centralizes sales content and guidelines in one place, allowing leads and other stakeholders to validate content and ensure proposals aren’t built on an outdated version from five years ago. And because all that data gets saved, you’re never starting from scratch. Every proposal builds on the ones that came before.
Sales teams no longer need to click around a confusing interface or wrangle a Google Doc into something that looks professional. Proposal automation software can use chatbots that clearly understand natural, human language, so your sales reps can make edits just like they were talking directly with a designer.
Proposal automation software integrates smoothly with your emails, client data, your CRM, and other tools your sales team uses. That means AI agents and chatbots can pull from phone calls, notes, contact information, and more. By integrating directly with the tools you use every day, proposal automation platforms can build better proposals without asking you to find all the necessary information yourself.
To know the impact proposal automation software can have on your sales cycle, you first need to know what to measure. Below, you’ll find key metrics to track, benchmarks you can compare your own numbers to, and ways proposal automation impacts these metrics.
This is the amount of time your team spends on creating proposals, on average. According to data from Loopio, top-performing sales teams spend 33 hours creating proposals in response to an RFP. Proposal automation software can reduce this time significantly without negatively impacting win rates.
Approval cycles depend on the type of client you have and your industry, but here are some general benchmarks:
Proposal automation software can streamline approvals, help you shift from sequential approvals to parallel approvals, and overall shorten your approval cycle.
Accounting for some variance based on industry and organization size, most deals close three to 14 days after a proposal is received. That time depends heavily on the investments you’ve made in drafting clear proposals that directly address a prospect’s needs, and proposal automation accelerates this process dramatically.
Sales cycles can vary significantly depending on industry, organization size, and other factors. A typical sales cycle, for example, can range between 84-102 days, with smaller organizations skewing lower on that range and enterprise organizations pushing the upper limit.
Implementing proposal automation software for the first time? Here’s a quick look at what you can expect.
This phase sets the foundation for everything that comes after. Auditing your process helps you identify the places where you most need proposal automation, while establishing metrics will allow you to measure success and correct issues as you go.
You can go even deeper in your audit and audit the time each sales rep spends on proposals, comparing that to their performance in other areas. That way, you can gauge the impact increased admin work has on your top reps and get a better sense of how proposal automation improves the way they work.
When you first roll out a platform, you’ll want to map out a simple pilot project to test it with. That might mean training just a few sales reps on the platform and supporting them as they create proposals for a few prospects. Review and evaluate the process as you test the platform, and slowly integrate it with your CRM and other systems.
Once your initial pilot project is complete, you can train your whole team on the new tool and roll it out in full. You’ll need to account for an initial transition period, in which reps might be tempted to use old processes before the new tool’s impact is proven. Plan to create supporting documentation and host extra training sessions as needed.
After a few months of using a proposal automation tool, you can usually identify potential improvements in how you use it. Optimization is an ongoing process, where you discover new ways to use a tool, scale its use to other departments, and implement new features as they’re released.
The advantage of a proposal automation tool like Cobl is it’s simple enough for individual reps to use without any IT help, meaning you can start using it quickly, see its impact, and adjust the way you use it. Then, you can share it with your team and improve the way everyone works.