How We Repurposed Our Stack for ABM and Saved 50% on MarTech Cost

At CaliberMind we see the business results of running account-based marketing every day with our customers so when it came time for us to implement ABM we decided to drink our own champagne. Below I’ll share the marketing challenges, the decision making process and the solution we implemented to help other marketing teams on their ABM journey.

ABM on a Budget

Most marketers associate ABM with mature firms which can dedicate a field sales team to large named accounts but the truth is that ABM makes perfect sense for startups as well, where customer development is critical as well as landing the “right” reference clients. The problem is that even venture backed startups probably can’t afford the complexity and overhead that come with a fully featured ABM platform. ABM platforms just like their previous generation Marketing Automation Platforms, take time to integrate, implement and train your marketing and sales team.

ABM is a Data Problem

There are also different types of ABM, if you are just looking to do Strategic ABM on a 1:1 basis with 1-10 strategic accounts, you should be just fine with your existing CRM & MAP. However, doing ABM Lite with 10-100 accounts and moving into Programmatic ABM with 100-1000 or more accounts usually presents a data problem. Salesforce data schema makes getting account data on leads an operational headache, also when you create a new lead in your Marketing Automation Platform, there is no way to natively link that lead to a pre-existing prospect or customer account in Salesforce.

Another problem is that most companies are not ready to go all-in on ABM and toss their lead-based and demand generation systems out the door. In a recent survey by ITSMA 70% of the companies reported that they are using a mix of both Demand Generation & Account-Based Marketing also known as Hybrid ABM, or Double Funnel.

The ABM Challenge

When we set down with our marketing team to define their ABM requirements, marketing wanted to:

1. Run Hybrid ABM – use traditional inbound demand generation programs such as email nurture, SEM, SEO and retargeting for our target audience along side account-based marketing tactics such as direct mail, events and ABM ads for our named accounts.
   
   
2. Enrich leads with account data – treat account records as the source of truth for firmographic fields on leads, and match leads to accounts.
   
   
3. Identify high-value prospects easily – port over valuable account information to leads so fields such as account status, territory, or any custom account field can be used to more effectively score leads for sales. (Nothing screams marketing and sales alignment louder than marketing using sales-determined fields in SFDC to score incoming leads…)
   
   
4. Create hyper-segmented campaigns and reports – in addition to more effective lead scoring, marketing wanted to be able to leverage account insights to better segment audiences, personalize campaigns, and do more in-depth reporting to measure the success of our different marketing campaigns.
   
   
5. Reduce research time for sales – run effective lead-to-account matching so all those tracked insights on account objects in Salesforce are automatically ported over to incoming leads and contacts to save our SDRs time on researching prospects.
   
   
6. ABM on a budget – most ABM platforms on the market start at $30,000 for the year and can go as high as $100,000 with annual commits and that’s before you realize the full cost of ownership of implementation, training, staffing etc’. Our marketing team was looking to repurpose and leverage our existing tech stack.
   
   
7. Model Engagement – which companies are engaged and likely to buy.
   
   

Our Hybrid ABM Solution & Architecture

It’s been well-documented and researched that 90%+ of visitors to your website don’t convert. And with a website visit often being a strong intent signal of someone interested in your product or solution, we were missing out on a number of opportunities to engage with people and companies that could benefit from our solution. We weren’t interested in just running demand programs to any and everyone that visited the site. We were much more interested in our key target accounts (or ABM).

At first, we looked at a series of ABM platforms in the MarTech space, but decided that it would be much more cost-effective and efficient to “Convert” our current CRM and MAP platforms instead. So we decided to run an “ABM Visitor Intelligence” play built on top of our CaliberMind Customer Data Platform.

Here’s a step-by-step guide to how we deployed a successful hybrid ABM solution. The diagram below looks complex and it is, but we’ve built this logic directly into the product so you don’t have to build this out yourself.

Identify Anonymous Visitors
Identify which companies are visiting the www.calibermind.com website and filtered out the noise of internet providers, employees, and spam. We’re left with a clean list of real companies.

Auto-Check All of Our Databases
CaliberMind auto-checked our Salesforce and Marketing Automation systems to see if there was a known account in the system(s). If an account didn’t exist in the database, we’d auto-create a new account and enrich the account with the information we needed (employee size, revenue, location, industry).

Score Accounts Based on Fit
Once the list of accounts (known or net-new) existed, we were able to then use CaliberMind to run these accounts against our Ideal Customer Profile model and score them based on “fit”.

Here’s a quick rundown on how we built our Fit Account Scoring Model using data from Clearbit:

Add Key Personas to Target Accounts
Once we scored our accounts based on fit, we’d leverage CaliberMind to see if we had the right personas and contacts on the account. If not, we’d get new target contacts through a prospecting tool embedded in CaliberMind. We’d now have the right people associated with the target account.

Surface “Fit” Target Accounts
The output of our account scoring model was a list of target accounts that met a specific threshold. For us, we bucket target accounts into different layers:
A Accounts – Strategic Accounts (Score = 80+)
B Accounts – Inbound Target Accounts (Score = 50-79)
With our account scoring model in place, we built a series of reports to be able to surface the right target accounts in the right territory for the sales team.

Run Targeted Programs and Alerts
Once we had the right contacts at the right target accounts and the information was surfaced to the sales and marketing teams we ran a series of different programs:

Marketing ran targeted email and advertising programs on all “B – Inbound Target Accounts”. We also ran air-cover for “A – Strategic Accounts” to ensure we had the proper ad and retargeting coverage to support sales. If we had enough data, we could build segments within CaliberMind to create custom audiences for our channels (for us this was LinkedIn, Facebook, and Google).

Sales used the real-time reports (specific to territory and rep) to ensure they were following up with all engaged accounts currently in the pipeline. If a new “A” account came in that wasn’t in the current pipeline, the sales team member had options: they could choose to run a series of emails directly from their outbound prospecting solution (Outreach) or place the account and subsequent contacts on a marketing email drip.

Automated As Many Processes As We Could
Knowing we purposely had a lean team and multiple priorities, we implemented and automated as many processes as we could:

Lead-to-Account Matching
Auto Account Scoring
Program Performance Alerts
Sales Alerts to Sales & Slack
Key Account Engagement Alerts
New Account Visit Automation & Alerts
Marketing Forecast Reporting
With all of this automation, we could focus on what really mattered: how to engage and delight prospective customers at each step of their customer journey.

Track Real-Time Account Engagement
With our programs and campaigns in full flight, we needed to ensure that we were keeping close track of engagement from the programs. But, because oftentimes we were targeting multiple personas/contacts at an account – we weren’t interested in just scoring leads. Instead, we aggregated lead engagement at the account level. Now, we were able to track the account engagement instead of the individuals.

In addition, we alerted the sales team in real-time (both Salesforce and Slack) if a target account and contact was engaged.

With an ability to track account engagement AND fit, we were able to quickly prioritize which accounts to follow up with. Sales was thrilled that they had this real-time insight.

Here’s a report we built in Salesforce for our sales team (with sheltered data):

The Initial Result
Once our “ABM Visitor Intelligence Play” was up and running for a relatively significant period of time we saw:

1. A 38% increase in engagement across the funnel with our target accounts
2. A 15% lift in conversion rates from our hybrid ABM and demand stage model
3. A sales team that could engage and communicate in real-time with their best prospects
4. A significant increase in net-new customers and new ARR