I was talking with someone who was in the process of building comp plans for next year and they had a number of challenges regarding reps who handle only renewals and upsells at time of renewal. We referred to them as “Renewals Reps” and I’ll do the same in this article.
Below are some of the challenges they noted along with my feedback:
Challenge: We have always done individual quotas for Renewal Reps. How would Team quotas play out? The issue we run into with individual quotas is the constant potential quota adjustments for renewals that are mis-categorized or “Dead on Arrival”.
My feedback: Team quotas are used to drive the behavior of teaming. If your Renewals Reps work independently, you don’t want to drive that behavior. Instead, I recommend working to identify what makes a renewal miscategorized or DOA and fix the root cause instead.
Challenge: We don’t want the rep to take a hit for events completely out of their control. At the same time, I can’t have a full-time person constantly making individual quota adjustments.
My feedback: The need for constant individual quota adjustments makes me wonder if you’re assuming a top-down model. You need to build bottom-up, too. Given the assumptions we can make about quota attainment (example: roughly 60% of reps make quota) and rep ramp time (example: 6 months to productivity), you can work out how many Renewals Reps and at what quota-per-rep it would take to achieve zero churn – or net negative churn which is the real goal.
Challenge: If a renewal is due on Sept 30th, it matters that it comes in on or before the 30th and not Oct 1. How can we drive renewals to close in the right time period?
My feedback: Consider automatically creating renewal Opportunities in your CRM 90 days before the renewal is due, or whatever the high-end of your average sales cycle for renewals is, with a close date in the appropriate period. Also automatic: assign the Opps to the relevant rep and push them into that rep’s forecast as best case/most likely (not commit). Then the reps will essentially work from their forecast as their “queue” of renewals.
Challenge: Finding the right split between Renewal (Retention) and Upsell. Currently we are 80/20 as we want to emphasize retention and we’re not sure if a different mix would be more appropriate.
My feedback: Remember that comp drives behavior. If you want to drive a reduction in churn, you need to over-comp on renewals and contract length. If you want to drive upsell, you need to over-comp on upselling.
Challenge: What about incentives for multi-year renewals as long as the ARR stays the same and discount does not increase? We don’t want reps giving additional discounts to lock customers into multi-year terms.
My feedback: Customers generally expect discounts for multi-year terms. There’s nothing wrong with not falling in line with that expectation but you need to keep it in mind. Plus, cash now is usually better than cash later. Generally speaking, if a reasonable discount means winning a multi-year contract, I’ll take the win.
I caught up with someone whose SaaS platform has an entry price of $20k. Their products were starting to really sell in the mid-market and enterprise space. As they moved upmarket, they felt the need to re-evaluate their discount strategy for these deals, and they asked for some advice.
Assuming the question of “are we going to discount to win deals?” has been answered “yes”, the first thing I’d do is pull in your finance team. You as a company need to determine the maximum discount the company can withstand on any one deal. Your finance team can help with this. In fact, their input is vital, because your ability to discount is tied to financial factors. Metrics like customer acquisition cost (CAC), cost of goods sold (COGS), customer lifetime value (LTV), net present value (NPV), and your cash flow needs are all critical to building a discount strategy.
Work with your finance team to build the case and get CFO sign-off. Get it in writing.
The reason I recommend determining this max discount as your first step is that all the numbers below will be different whether you can bear a max discount of 88% or 18%.
Once you have a handle on the max discount you can withstand, you can move on to the following:
Create a table (e.g. list/chart, not furniture) of your max discounts relative to contract duration. The max discount you can bear on a 1-year contract will be different than on a 5-year due to NPV, your own returns on cash, etc.
Determine breakpoints for approvals and who (the role, not the individual) needs to be involved at each approval tier. This comes down to crunching data and then working with a cross-functional group of sales, finance, and executive leadership to codify e.g. devise and implement a standard of discount tiers and an approvals matrix.
Create one or more reports, and/or a dashboard, to monitor:
Discount requests and requests outstanding
Approval durations / “close time” (how long approvals take, so you can factor into your sales cycle time)
Deal size and discounts relative to those deal sizes
Contract duration and discounts relative to those contract durations
Establish a regular review process to make sure you’re staying on sound financial footing.
As your data on discounts and discounting matures you need to refine your model and your enablement practices relative to onboarding and ongoing development of individual sellers and sales leaders.
One benefit we got from this was being able to provide better guidance on deals. We’ve got a decent understanding of the combination of deal size, contract duration, and discount rate as those relate to customer type (by size and industry). This means we know (i) what a win-win-win deal looks like, meaning us-partner-customer and (ii) what a bad sales rep looks like, meaning a salesperson who doesn’t know better than to compete on pricing (as opposed to selling on reducing/eliminating customer pain).
A detailed example with commentary is below:
We can withstand a maximum discount of A%
We’re sold exclusively through partners and the partner who registers a deal is guaranteed a percentage so they can markup; assume a guarantee of [A / 4]%
Let’s assume A is 100. It’s not, or we’d be out of business, but we’ll use 100% for simplicity’s sake
The above means the partner with deal reg gets 25% (again, I’m shooting for simplicity here)
We aren’t going to require approvals at 25% or our sales cycle time would skyrocket
We ran the numbers on a couple of years of deals and found the standard deviation was +/- 10, meaning the vast majority of our discounts fall into a range of 15-35%
To constrain discounts to fit within that standard, we’d set our first breakpoint at 35%, meaning approval is required by the seller’s direct manager to do a deal at a discount of 35% or greater
From there, consider setting additional breakpoints by the discount tiers you determined. Continuing with our example:
We set additional breakpoints at each 5% increment up to 50%
35% and above requires approval from the seller’s direct manager
40% and above requires approval from that manager’s Area VP
45% and above requires approval from that AVP’s “Geo VP” (in our case that’s AMER, EMEA, APAC)
All deals at or above a 50% discount require sign-off from our CRO and our VP Finance
All deals at or above a 70% discount require sign-off from our CFO
We use an all-in and first-rejected approval model, meaning all approvers must approve and the first rejection is a global rejection of the offer (the seller needs to try, try again)
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