When people hear "document management," they may think about contracting. While losing a contract is one of the more embarrassing conversations to have with a long-term customer, it's far from the only document type prone to error and inefficiency.
Companies have reduced their sales development departments and marketing budgets, which shifts the responsibility of generating pipeline back to the account executive. According to a Salesforce survey in September 2023, only 28% of B2B SaaS account executives expected to hit quota by the end of the year. We're adding to their many distractions instead of giving sellers more time to pursue potential customers. Finding ways to streamline the tasks they regularly perform is a great way to free up time – and document generation is no exception.
There is a lot of potential for productivity gains in the document automation space. Content material ripe for automation include:
With help from revenue operations, sales enablement can identify the sellers who are the most successful at different points of the sale. Once these people are identified, sales enablement can shadow them, take the presentations they produce and documents they rely on (or would like to rely on), and make those documents a repeatable template for the rest of the department.
Revenue operations is also well-equipped to figure out how to operationalize the onboarding process and identify any needs for customer-facing documentation.
We'll focus on identifying inefficiencies, using metrics to spot the efficient frontline representatives, and finding a solid document pool to pull from that will speed up your document automation journey.
Identifying inefficient areas should be done through qualitative interviews and data analysis. We've found qualitative interviews to be a great jumping-off point for determining what is potentially sucking up sales and customer success bandwidth.
Start by interviewing managers of frontline representatives. While the CRO or VP of a go-to-market team may have some interesting tidbits of information, they typically try to stay out of the tactical details. The frontline managers will know who is complaining about which step in the process. They'll also be able to point out who they think is the best at specific tasks throughout the customer lifecycle.
Once you've interviewed the managers, it's time to validate their theories with data. Don't worry; after this process, you'll interview a few individuals on the frontline and perhaps some customers to get the details.
To identify sticking points in the sales process, determine how consistently the teams use opportunity stages and forecast categories. Do they have a standardized process that is adopted by each team? Do they use the stages reliably? Or do they lean on forecast categories?
If your sales team uses opportunity or deal stages in your CRM, it's important to analyze the average time it takes for one stage to progress to the next. It's also even more vital to study conversion rates! However, we'll only be visualizing time in stage. Both should be reviewed side-by-side in practice.
HubSpot stamps deal stages for you. You may still need to export the data into a tool to easily create pivot tables that slice the data by sales rep, manager, territory, deal type, and final stage (Open, Won, or Lost).
In Salesforce, you can use the opportunity history table to figure out the minimum date each opportunity reached a stage by creating a table with a list of opportunities with the details you want to analyze (sales rep, manager, territory, opportunity status, and/or team are good starting places) and performing a MINIFS formula or MIN formula with nested IF logic (check this article out for a how-to).
Of course, all of these steps can be avoided by using custom fields on the opportunity object and flows.
Pro Tip: Don't forget to talk through how your company wants to handle a closed lost opportunity, stage skips, and stage regression (moving a later stage back to an earlier stage).
We recommend looking at five quarters' worth of data (or more depending on your average lifecycle – you'll notice the average days in stage dropping off suspiciously if your sales cycle isn't over) and summarizing your information by AE, sales manager, opportunity status (Won, Open, Lost), and product type.
Once you have the average number of days in stage summarized when the opportunity was created or qualified (whichever the AE is supposed to use to signify a "real" opportunity), you should first look at the average time in stage by opportunity status. In most organizations, Won will be your shortest time in the stage, and Lost or Open will be very long. If Open is longer than Lost, this signals that your sales team needs to clean up their pipeline regularly, and you have some old deals throwing off your averages.
Once you've determined what your average time in stage *should* be, you can start to layer on account executive data. Some reps will be great at getting a second meeting. Some will generate a lot of interest midway through the sales cycle. Others will be great at closing the deal. It's unlikely that a sales rep gets everything right (but it happens).
After identifying the most efficient sales reps, it's time to validate that information with your frontline managers. Then, talk to the sales reps or pass their information on to the sales enablement pro to work on document collection and deeper inspection.
Customer success can be more subjective. You'll want to look at churn percentages by onboarding specialists and account managers. You'll also want to layer on product data like any metric your organization uses to help determine adoption and product satisfaction.
It's easy for people to get really excited about using AI to personalize documents and modify text. At this point, we recommend using AI only if your sales team is committed to editing and reviewing documents to avoid embarrassing situations (typos, inappropriate language, inaccurate data, etc.).
Other things you'll want to explore:
Before purchasing a tool, it's critical to honestly evaluate whether your CRM data, like product information and company details, is clean enough to support an automated process. If not, the prospect of freeing up sales reps to sell more may motivate your finance team to integrate their ERP or purchase a better enrichment source.
Creating templates and plugging in a tool is only half the battle. The real work is convincing your frontline representatives that the new documents will help them be more successful than the documents they use today. You'll also need to prepare on-demand training materials to help the team get the most out of the document automation tool after it's rolled out.
For more on change management, check out this article.
For more on document management automation, check out this report by Nintex.
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