Measuring success in dynamic books

AI, covid, and the wide availability of customer data has forced B2B RevOps teams to take a look at how they deploy their sales quota capacity. And dynamic books can help. We did the research to help you determine what success looks like with a dynamic model. 

Average contract value (ACV)

• Total revenue from contracts: Find the sum of the revenue generated from all contracts within a specific period.
• Number of contracts: Count the total number of contracts signed within the same period.
• Divide: Divide the total revenue by the number of contracts.
• Compare Your ACV: compare your ACV to previous years, quarters, and other metrics (like CAC).

Industry benchmark

There isn’t a universal benchmark for ACV because it depends on what is being sold. However, using it to compare to historical data will give your sales team an idea of whether the deals being converted are bigger or smaller than before. Smaller or stagnant ACV means that the deals being prioritized are likely not large enough and changes need to be made in SDRs’ assigned accounts.

“You’re never going to get it right the first time, creating channels to get feedback and figuring out how to implement it is how this works, however, this has been my favorite transformational system change for our business...” - Nora Soza, Sr. Director, GTM Strategy at Box

Activities

Knowing how your sales reps are engaging with their accounts can tell a sales leader many things, including: appropriate amount of accounts to assign, how many touchpoints between sales cycle stages are needed to close, and likelihood to close based on multi-threading. Ensuring your team is hitting the benchmarks for activity or touchpoints and multi-threading will help you to stop overloading your reps with too many accounts, prevent account hoarders, and improve your win rate–with limited complaining about inequitable account assignments.

Industry benchmark

• Multi-threading: 2-3 contacts per account, based on the average B2B SaaS buyer committee that usually comprises  people
• Activity: 70 tailored emails a week, 40-50 calls a day
• *Bonus* Accounts assigned: 70-125 per rep

Lead response time

We’ve all heard of this lead response metric, but are we really making strategic decisions based on it? We should be. Lead response times have proven to be an indicator of strong win rates for those who respond within one day. Currently, the average response time is 42 hours for B2B SaaS companies, but that is not the most effective time frame. Lead qualification dropped to just 10% for companies that waited more than an hour to respond. A dynamic sales process will automate your lead routing to give real-time updates when a new account is assigned to a rep so that they can quickly prioritize their day to reach out as quickly as possible.

Industry benchmark for B2B SaaS sales

• Good Response Time: < 20 hours
• Better Response Time: < 1 hour
• Best Response Time: < 5 minutes
• Current Average Response Time: 42 hours

Sales quota attainment

Quota attainment can really make or break a team of reps because inconsistent attainment can burn out your team and slow down pipeline due to frequent training of replacements. A dynamic sales model will make tracking these numbers easy and give you the opportunity to fix the problem faster. A team struggling to hit a quota or severely different numbers between sales reps is a good sign that either an rep needs more training or that the account pools are not equitable between them. With a dynamic sales model, the likelihood of it being unequal account pools is very small since they are going to be selected and distributed based on your ICP and customer lookalike scores instead of static territories.

Industry benchmarks

• Ideal attainment: 67% of SDRs should hit quota attainment
• Current average attainment: 51% of SDRs hit attainment
  
  

Time allocation (for reps)

Inefficient time management in sales teams leads to wasted resources and missed opportunities. Reps often get bogged down with admin tasks, research, and figuring out which accounts to prioritize, which pulls them away from the real goal—selling. By automating these processes, sales teams can streamline their workflows and ensure that reps focus on high-value activities. AI research tools quickly gather relevant data, and the account prioritization identifies the most promising leads. This not only boosts productivity but also improves overall sales performance, allowing reps to dedicate more time to building relationships and closing deals, ultimately driving revenue growth.

Industry benchmarks

The average rep is spending their week like the following, according to Salesforce surveys. Note: these numbers do not focus on teams using dynamic books, so it’s important to note that reps typically spend less time researching, prioritizing, and on admin tasks in a dynamic books model.

• Researching: 4 hours
• Prospecting: 3.5 hours
• Prospect Meetings: 7.9 hours
• Lead Prioritizing: 3.6 hours
• Admin/non-selling tasks: 21 hours

Sales cycle length

Prolonged sales cycles reduce efficiency and strain cash flow, hindering a company’s ability to grow and meet financial goals. Automation and AI can streamline sales processes, research time, and optimize workflows, boosting overall productivity. If a sales leader notices that the sales cycle is taking longer and longer to close, they should first analyze the sales process to identify bottlenecks or manual processes. Implementing automation for repetitive tasks, using AI for data-driven insights, and continuously training the sales team on best practices can help shorten the cycle.

Industry benchmarks

The sales cycle usually depends on your ACV:

• < $5k ACV = 30 days
• < $25k ACV = 90 days
• < $100k ACV = 90-180 days
• > $100k ACV = 3-9 months
• > $500k ACV = 6-18 months
• *bonus*: Startups have seen a 24% increase in sales cycle, with the biggest increases in enterprise deals, which are 36% longer (2023, Tomas Tunguz)

Time spent on annual sales planning

When there’s no solid strategic planning, outbound sales can get stuck in a rut, making it tough to pivot when the team isn’t hitting targets. AI tools can come in handy by assisting in data analysis, conducting research, enriching data in real-time, and correcting old data, enabling it to create accurate account prioritization. This frees up time for sales leaders to focus on high-level strategy with trusted information. Additionally, automation in dynamic sales models ensures that accounts are appropriately distributed and prioritized, preventing high-value leads from being neglected. With dynamic books, sales teams maintain flexibility, effectively target top accounts, and continuously optimize their outbound efforts.

Industry benchmarks

The average B2B SaaS company spends somewhere between 8-16 weeks on sales planning and strategy each year. 

A B2B SaaS company with a dynamic model spends somewhere between 4-8 weeks.

Bonus: qualitative metrics

The following metrics don’t have industry-wide benchmarks, but they are still processes and tasks that should be monitored to ensure efficient and effective sales team motions.

Sales and marketing alignment

Pain Point: When sales and marketing aren't on the same page, it can really mess things up—campaigns fall flat, leads slip through the cracks, and everyone ends up frustrated. If these two teams aren't working together, it’s a recipe for wasted time, resources, and missed opportunities. Plus, it can seriously hurt conversion rates, leaving both teams feeling like they’re spinning their wheels.

Solution: To close the gap between sales and marketing, it’s key for sales leaders to set up integrated planning and keep the communication flowing between both teams. Dynamic books make this easier by offering shared metrics and research, so everyone’s on the same page and aiming for the same goals. When you establish joint KPIs and hold regular check-ins, it helps both teams fine-tune their strategies and boost lead quality.

CRM data maintenance

Pain Point: Inaccurate or outdated CRM data can severely hamper sales strategy processes. Bad data means you might miss out on opportunities, waste time on inefficient processes, and end up with strategies that don’t hit the mark with your top prospects.

Solution: Automated data entry and AI-driven data cleaning are critical for maintaining up-to-date and accurate CRM information.With dynamic sales software, AI takes care of regularly cleaning up your CRM, fixing any mistakes, and getting rid of duplicates. This doesn’t just make decision-making easier—it also smooths out your sales processes and boosts overall efficiency.

Lead scoring and prioritization

Pain Point: Poor lead prioritization can lead to missed opportunities and wasted efforts on low-potential leads. Without accurate lead scoring, sales teams may focus on the wrong prospect accounts, resulting in lower conversion rates and lost revenue.

Solution: Dynamic sales models take lead scoring to the next level by using AI to analyze tons of data points against their ICP. These models build scoring systems that adjust to new info and market changes, keeping lead prioritization sharp and on point.

Flexibility for changing plans

Pain Point: Inability to pivot quickly in response to market changes can be detrimental to a sales team's success. Sticking rigidly to outdated plans can result in missed opportunities and a failure to meet evolving customer needs.

Solution: Staying flexible is key, and that’s where adopting an agile approach and using real-time analytics comes in. Dynamic sales software makes it easier to adjust quickly based on live data and feedback. Reconfiguring prioritization of accounts because you’re behind the books can be reduced to a few days with AI, automated team notifications of changes made, and books automatically updating to include the new parameters and strategies.  

Dynamic books: conclusion

In today’s rapidly evolving market, sales leaders face numerous challenges that require agile and innovative solutions. Adopting a dynamic sales model equips sales leaders with the tools needed to navigate today’s complex market landscape. It provides the flexibility to adapt quickly, the intelligence to make data-driven decisions, and the efficiency to maximize productivity. By capitalizing on AI and automation, sales teams can stay ahead of the competition, close more deals faster, and drive sustained growth. 

Learn more about how dynamic books can transform your sales strategy.