Here is Part 6 of The Marketing Performance Index, featuring an in-depth analysis of marketing performance over eight consecutive quarters. In my previous five blogs on the Marketing Performance Index (MPI), I explained the genesis, design and definitions for the 24 key metrics it tracks across Market Presence, Brand Strength and Pipeline Health, along with tips and techniques to improve performance in areas where any particular score is below industry benchmarks and/or target results.
Now, I’m going to examine the results of driving performance improvements over a two-year period while I was CMO at Emburse, and share some thoughts on how to drive predictable pipeline performance (the one metric every CEO, investor and board cares about). As with business in general, it’s rare, if not virtually impossible, to achieve linear growth across all metrics on a continual basis. There are many factors that influence marketing and business performance, from staffing, to investment, to collaboration, competitive and market dynamics, in addition to macroeconomic, environmental and geo-political influences. The annotated chart and below illustrates this.
My team and I helped launch Emburse (as a branded house representing what were previously seven separate businesses) in January of 2020, just before the world virtually shut down due to the global outbreak of COVID. With our primary offering being a SaaS-based Travel and Expense offering, it’s no wonder business was slowed dramatically. However, due to an aligned executive team embracing an agile approach to go-to-market, product and services innovation, the company quickly diversified revenue streams and regained momentum by the end of the year.
As I’ve noted, the MPI tracks 24 key metrics, and when you measure over a longer period of time, it’s clear that not all metrics can improve quarter over quarter, individually or in aggregate. In the case of Emburse, I’ve annotated what I consider as some of the key drivers for either steady performance, overperformance or under-performance. By Q2 of 2020, there was not much we could do (and we tried) to revive declining bookings, at least until people started traveling more, so you can see a dip in our overall score. By the third quarter of that year, however, inbound and ABM tactics helped boost performance, followed by a successful re-platforming of our global Websites, a more unified brand strategy, and more integrated marketing programs all contributing to better overall performance.
By year two, we were well on the way to executing a cross-functional approach to cross-sell. By orchestrating a coordinated approach, including team alignment, shared goals, sales enablement, compelling content, timely customer communications, value-based selling and dynamic offers, we delivered nearly a 100% increase in cross-sell bookings.
We were also gaining momentum in our ABM approach (leveraging ICP analytics, target account selling, marketing qualified accounts with lead scoring and routing, and intent-based account prioritization. As a result, we experienced uplift in both net new and expansion (existing customers) sales.
However, we hit a wall the following quarter due in part to the impact of continued business disruption and staffing setbacks. And once again, we rebounded in the following quarter, largely due to the successful launch and subsequent customer adoption of new products and services.
Marketing Performance Index- 2 Year Tracking Results
| Period | Score | Change (%) | Key Drivers |
| Q1, Year 1 | 62 | n/a | n/a |
| Q2, Year 1 | 60 | -3% | COVID |
| Q3, Year 1 | 62 | 5% | Inbound |
| Q4, Year 1 | 67 | 6% | New Website |
| Q1, Year 2 | 81 | 21% | Cross-sell |
| Q2, Year 2 | 90 | 11% | Intent Platform |
| Q3, Year 2 | 85 | -6% | Disruption |
| Q4, Year 2 | 94 | 11% | Product Launch |
| 2 year gain | +32 | 52% | – |
Over this two-year period, including a couple of significant dips in the more challenging quarters, our Marketing Performance Index score increased more than 50%, or about 25% per year. A simple rule of thumb for tracking pipeline creation and growth is that it needs to at least be equal to the bookings and/or revenue target growth percentage. So, if the annual target is to grow bookings, especially for net new logos, by 20%, it stands to reason that pipeline must grow by at least that percentage. It’s possible to achieve higher bookings growth percentage than pipeline growth, but that would require increasing lead conversion, opportunity close rates and average opportunity values, and likely all three together.
My teams and I have spent hundreds (or perhaps thousands?) of hours over the last several years working hand-in-hand with our colleagues in Sales and Sales Development (ADR, BDR, or SDR) to refine our go-to-market approach, programs, tactics, metrics and counter-measures to optimize pipeline creation, conversion, progression and close. That’s a key reason why I included four Progression metrics in the MPI: MQL to SQL (Marketing Qualified to Sales Qualified), SQL to SQO (Sales Qualified Lead to confirmed Opportunity), Close rate (from Stage 1 opportunity to Close) and Win rate (head-to-head win rate vs. top competitors). Companies need to track Sales efficiency together with Marketing efficiency, so we can improve results across the board.
Some of the strategies and tactics my teams and I have incorporated to help drive more predictable pipeline performance include: weekly GTM meetings (Sales, Marketing, BDR) to review results, successes, setbacks, brainstorm new ideas, assess lessons learned; real-time dashboards to report on the key performance metrics, by program, by tactic, by team, by region, by segment, by stage, etc.; pipeline maturation projections – how long will it take for pipeline to convert to closed won or lost; account based engagement – what is the relative level of engagement by account throughout the buyer’s journey, especially in comparing the “happy path” to closed won vs. any other path to: pushing out deals, no decision or closed lost opportunities. Furthermore, I would urge Sales and Marketing teams to agree to weekly pipeline inspection and hygiene and to diagnose and problem solve in unison. Too often, I’ve been at companies where the pipeline multiple (needed to achieve the booking target) was adequate at the beginning of the quarter, but quickly deteriorated (closed, no decision, pushed out, closed lost, etc.) in the first few weeks. Pipeline hygiene, just like pipeline creation, should be a daily discipline, or at least examined with rigor on a weekly basis.
One final recommendation. Whether or not you have a dedicated data analyst on your team, it’s critical to build projective models, with a high degree of customization if needed, to project how much pipeline, based on historical performance, is needed by team, by segment, by stage, and also determine the time equation from initial qualification to closed won, or lost. This way, you have a better leading indicator of your likelihood to achieve bookings targets.
And lastly, we’re in an exciting time with the rapid innovation of GenAI across all function of the business. My teams and peers have been experimenting and adopting dozens of GenAI tools over the past couple of years, and I expect we’ll see a variety of new tools leveraging existing platforms (e.g. CRM, MAP, Intent Platforms) and new approaches to leveraging AI and analytics to optimize the entire GTM motion, from targeting (ICP) to account development (ABM) to pipeline creation, prediction and optimization.
In my next blog, I’ll be sharing sample MPI scores from CMO peers, along with strategies and tactics to improve outcomes. In the meantime, if you’d like to take the MPI assessment while I’m developing the online, self-serve version, send me a note and I’d be happy to arrange gratis.
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