How to Deliver Credible Marketing Pipeline Forecasts

• Christine
• January 12th, 2019
• CMSWire
• 0 Comments

Marketing owns the pipeline today. Not because sales is not performing, but rather because marketing owns most of the customer lifecycle touchpoints. In “The 4 Factors Defining Marketing’s Future,” we identified one of the biggest challenges facing marketers: the inability to deliver credible forward-looking marketing-generated pipeline forecasts. It’s what boards want and what the rest of the C-Suite needs to excel at their jobs. Historically, board of directors didn’t expect marketing to talk about owning pipelines and forecasts. If marketing presented at all to the board it was about branding. Today, all board of directors want to talk about are ROI, pipeline, funnel metrics, investment metrics and more. According to Ken Klein, who sits on a number of boards, “the ideal situation is if the CEO could measure marketing based on the pipeline generated, audit that number and the process, much like the financial books.” Part of the problem, according to Klein, is that board members lack the expertise in marketing to ask the right questions.

Bringing More Science to Marketing

CEOs stress that marketing needs to become more scientific. “Marketers need to embrace that. Funnels should be viewed as a scientific experiment because not every channel or lead is equal,” said Henry Schuck, CEO of DiscoverOrg, a prospect data and B2B intelligence solution. “It takes time and iterations to get the data, process and reporting correct to yield credible marketing generated pipeline forecasts. It took us two and half years.” Marketers don’t disagree — they are trying to deliver credible pipeline forecasts. Doing so would help their credibility, secure more funding, and level the power equation in organizations. What’s holding marketers back is not lack of desire but a lack of knowing where to start and having the right data. In talking with CMOs who have mastered credible pipeline reporting, they stress that four foundations need to be in place first:

1. Agree on the percentage of revenue that marketing will source.
2. Ensure marketing and sales op systems correctly capture leads for each channel.
3. Analyze past 12 months of lead distribution by channel for consistency, seasonality and identify unpredictable channels, i.e., social algorithmic changes.
4. Identify the internal skilled resource(s) who own managing forecast data and process.

However, marketing can’t do it alone. They need sales to be an active partner in the entire process. Sydney Sloan, CMO of SalesLoft, a sales engagement platform, Schuck and John Fernandez, former VP of Revenue Marketing at Contently, all said it took them a minimum of two years to achieve pipeline forecasts that are within +/- 10 to 15 percent accuracy for the current and future two quarters. The benefits of reaching this level of accuracy is multi-fold. “It enables marketing to report with consistency to the board and that builds confidence,” said Fernandez. Klein half-jokingly shared, “If I started a company from scratch, I would focus on this part first. Let’s agree upfront on process, definitions of nomenclature, and what exactly gets added to the pipeline.” He goes on to say, “Marketing and sales need to have the same metrics. That way the right leads go to sales and it’s repeatable and formulaic.”

A Repeatable Sales Cycle Is Key

If your sales cycle has not achieved stable repeatability for at least four to five sequential quarters, you have no basis upon which to expect marketing to deliver credible forward-looking pipeline forecasts. And chances are high your sales forecast is not as credible (and predictable) as you’d like it to be. Your business model or market is not mature enough. Repeatability is important because marketing needs accurate and complete historical data as the foundation for predictive modeling. Without that, credible predictability will be elusive. That doesn’t mean you should abandon forecasting, rather you should use it to identify patterns.

How One Company Mastered Marketing-Generated Pipeline Forecasting

Contently, provider of a content marketing solution, has mastered marketing-generated pipeline forecasting. It is its primary means to manage the business and marketing investments. Fernandez built and managed five data models that became the cornerstone of marketing pipeline management.

• Customer Database: This database includes over 40 key attributes for every customer, both active and inactive. The Salesforce database is maintained daily to ensure every data element is correct and current. “The biggest problem these days is data. It’s grumpy and dirty,” shared Fernandez. “Analysis isn’t the problem, it’s data quality and veracity.”
• Historical Pipeline: Is a Tableau database of all past marketing and sales pipelines, forecasts and accuracy.
• Historical Lead Performance: Is a Marketo database of all marketing leads, campaign source, cost, time to lead conversion, number and cadence of subsequent touches, time and rate of pipeline conversion, deal value and win rate.
• Marketing Channel Analysis: This Tableau database combines the first three data models to track and report on marketing channel lead and engagement performance, spend and ROI.
• Marketing Spend ROI: This database “allocates every penny of marketing spend including discretionary, overhead allocations and fully loaded salary costs,” said Fernandez. “We use it to calculate Return on Marketing Spend as well as ROI for every marketing and sales team as well as channel. This shows the board we are responsible with money.”

Schuck suggested a good place to start is with a bottoms-up approach, which he considered a learning experiment. “You’re going to find data and process gaps. Channels — inbound, events, direct mail, email, syndicated content, PPC etc. — that everyone thought were productive but aren’t,” said Schuck. “As you go, fix and refine.”

5 Steps to Forecasting Your Marketing Pipeline

With your data in shape, you’re ready to forecast your marketing-generated pipeline:

1. Set your annual target of marketing generated pipeline revenue ($X) broken down by month to account for seasonality, if there is any.
2. Separate out “net new,” “renewal” and “up-/cross-sell” pipeline forecasts, as the three behave differently. According to Schuck, “Determine, by market segment, the average win rate (Y) and be specific if the win rate differs by product/solution, customer size and/or industry.” Sloan also stressed that forecasting blended business models, where you have multiple sales cycles, requires separate modeling and forecasting.
3. Determine your marketing "coverage" rate — most B2B vendors use four times. Meaning, marketing needs to generate four times $X for the year with a win rate of Y.
4. Define the historical spend and conversion metrics for each channel, which you’ll then use to forecast future spend pipeline results. “A key to success is making sure the channels are tightly aligned to the actions customers take at each stage in the buyers’ journey,” stated Fernandez.
5. Develop your marketing revenue-generated pipeline forecast. Use historical conversion to pipeline and win rates to forecast marketing generated pipeline by forward quarters.

What Can Throw a Forecast’s Credibility?

A lot of factors can throw off a forecast's credibility. Most of these are unexpected, like budget and channel mix changes. Revised forecasts need to account for the effect on leads by channel by time period but also the ripple effect on other channels, what Sloan calls the omnichannel effect. While marketers are talking about executing omnichannel campaigns, the reality is marketers still plan and spend in a channel-centric model. Her rule is to “stop investing in channels if there is no ROI (revenue) in six months of investing. Instead take a ‘fail fast’ approach to new channels. Switching to ABM or ABM list changes can also throw a forecast. Marketing teams need two or more quarters to understand the impact on historical conversion patterns.  Sloan has found that with ABM it’s best to focus on the number of opportunities to be generated versus revenue amounts. Going through this process inevitably brings up the topic of attribution models. Sloan is a fan of multi-attribution models to achieve visibility of conversion along the sales cycle. Schuck and Fernandez, not so much. However, all agree that the first and last touches are critical. Sloan advises companies to keep it simple.  “Don’t try to over-calculate the forecast, you’ll never get to the exact number.” The ability to present credible marketing generated pipeline forecasts is a game changer for marketing and the company. A key to success is routinely reviewing the pipeline forecast with the CFO and CEO.  Schuck suggested weekly meetings, so everyone understands the process and changes being made to marketing spend and the forecast model. First published in CMSWire.