The Moneyball CEO: Navigating Your Whitespace to Grow Revenue

Every CEO wants to squeeze more out of their investments in customer acquisition. And that’s particularly true in today’s market. Stock multiples have come down, especially for many business-to-business SaaS companies that are not yet profitable. In this environment it’s all about doing more with less, and hence we’re seeing the rise of the “moneyball” CEO. These smart leaders leverage predictive analytics to grow revenues with what’s already in their pipeline.

Before getting into how to identify this “whitespace” of untapped opportunities, let’s take a step back and think about what executives should be doing to drive revenue. If I were to encapsulate a go-to-market (GTM) manager’s key functions as an algorithm, it would look something like this (in pseudo-code):

Loop Until Fired():
1. Forecast_The_Business()
2. Identify_Gaps_In_Current_pipeline()
3. Reassign_And_Enable()
Repeat

Infer’s Automated Form Monitor for Marketing Operations

Infer’s Automated Form Monitor, which is a simple WordPress plugin, helps marketing operations teams periodically test their site forms to ensure they’re operating properly.

How to Use Infer’s Automated Form Monitor Plugin

If you’re unfamiliar with installing and activating WordPress plugins, please see this post in the WordPress Codex.

After installing and activating the automated form monitor plugin, you will see an Admin Menu option called Form Monitor (see left screenshot). To begin monitoring your site forms, click the Form Monitor option, then follow these next steps:

 

  1. Download this CSV template.
  2. Double click the .zip file, and open the CSV file in your preferred spreadsheet or text editor (Excel, Numbers, Google Sheets, TextEdit, etc.).
  3. You will see a number of columns in the CSV file. Create and fill out one row for each form you want to monitor.

Introducing Infer Form Monitor: How a Simple Marketing Challenge Sparked Internal Innovation

As it’s often said, necessity is the mother of all invention. Recently, we decided to re-architect our Pardot Marketing Automation, and as part of this project, we began looking for a way to test all of the forms on our website in order to make sure they were working properly. Any Marketing Operations person will tell you that the last thing they want to worry about is whether they are forfeiting leads because of a broken form.

As we looked to the market for a solution to this problem, we were surprised that none existed — and, certainly not one that worked easily with WordPress and Pardot. So, we kicked off an internal project to find a better way to monitor the health of website forms. The result was our brand new Form Monitor, which is a simple WordPress plugin that comes fully integrated with Pardot and can be downloaded on the WordPress marketplace.

In the spirit of idea generation and innovation, we want to share our learnings with our friends in the broader marketing community. So, we sat down with our Senior Director of Product Marketing, Sean Zinsmeister, to learn more about the inspiration for the plugin, how it takes a big load off MOPS, and lessons learned along the way.

Profile Management Product Updates: Account-Based Marketo Behavior Profiles, “Contains” Operator, and More

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Since releasing Infer Profile Management to general availability in March, we’ve been hard at work collecting and implementing our customers’ post-launch feedback into the latest release of the platform. We’re excited to share all of our newest product features and updates in greater detail below.

Account-Based Marketo Activity Profiles

We’re deepening our integration with Marketo to extend users the ability to build data-rich, account-based profiles using their Marketo Activity behavioral data.

3 Growth Hacks to Boost Revenue Upwards of 10%

This byline by Infer’s Sean Zinsmeister was originally published on the Salesforce blog.

Every sales leader, in every company, is searching for a killer growth angle. We all want to know how to squeeze more out of our pipeline. The best go-to-market managers differentiate themselves by pinpointing key segments where they can close deals quickly. However, this isn’t a code many people can easily crack. Whether you know it or not, your company is sitting on at least some “white space” of untapped opportunities that are already in your funnel. Few businesses realize how much potential revenue they’re actually leaving on the table, but we’re seeing more and more elite sales and marketing shops figure out how to turn pipeline gaps into revenue growth upwards of 10% – and I’ve had the privilege of learning from several of them.

One thing I’ve noticed in top-notch Sales VPs is that it all starts with how good they are at forecasting pipeline. But even when management is great at predicting how much revenue each rep and each channel will bring in, high-growth companies are never quite on target. That’s why identifying gaps is crucial to meeting sales goals. Once you determine where your team is missing the mark, you need to make adjustments quickly to address those gaps. This could mean reassigning territories, changing the makeup of the team, mandating training programs, etc. Good managers go through this cycle again and again to optimize and perfect sales motions until they hit or exceed their number.

The second stage in that sales management cycle – identifying gaps – is the toughest to nail, especially as a company evolves. But I’ve found that the gray area of discovering hidden gems already sitting in a CRM or Marketing Automation system is actually one of those variables that can have a large impact on the topline.

4 products Microsoft should build with LinkedIn

This byline by Infer’s Vik Singh was originally published on VentureBeat.

LinkedIN

Last week, Microsoft stunned the tech world with the largest ever software acquisition – the purchase of LinkedIn for $26.2 billion. While early news coverage has addressed plans to keep LinkedIn independent, there’s been little discussion about what exactly the two companies will do together. As someone who’s entrenched in the LinkedIn and Microsoft ecosystems, I thought I’d share four exciting products this acquisition makes possible:

1. Redefined business email

The quickest and broadest impact Microsoft can make with LinkedIn is to redesign its Outlook interface. The companies could easily bring LinkedIn insights, profile photos, etc. into the email experience (similar to whatRapportive offers today but with a seamless, actionable approach). Outlook could even show recent updates and thought leadership pieces from a particular profile as talking point suggestions to automatically populate in an email when selected.

Microsoft could also add automated email filtering and prioritization features with folder recommendations that improve email productivity. Imagine if you could get emails that meet certain criteria — say they come from a particular job title and are second-degree connections with at least 500 connections themselves — to stick in the top of your inbox until they receive your attention.

2. Universal identity

There’s no doubt that LinkedIn’s biggest asset is its social graph with data about virtually everyone in the business-to-business (B2B) world. Ask any salesperson — it’s the business data they trust the most. Social proofing goes a long way. More importantly, when someone moves from one company to another, their LinkedIn identity remains intact. By rethinking the sense of a “user” in theMicrosoft Graph (a focus at the company’s Build 2016 developer conference a few months ago) around their LinkedIn profile, Microsoft could capture more activities about that individual from before and after they joined their current company.

As a result, the Microsoft Graph would become richer, blending LinkedIn information and updates with corporate activities like emails, calendar events, etc. Companies could also leverage LinkedIn credentials for single sign on (albeit there are enterprise security challenges here). This would ultimately be a better experience, because rather than needing new credentials every time you start a new job, you could use the login you already remember (and won’t forget, as LinkedIn will always be a key part of your career). We might even see an evolution in messaging, and the approach of sending emails to corporate addresses that may no longer be valid will become old school. Instead, Outlook integration could make sending messages to each other’s LinkedIn accounts feel seamless.

LinkedIn’s social graph could also spruce up Microsoft’s bot framework, which got a lot of attention at the Build conference as well. More apps that enable personalized, compelling conversations on top of Microsoft platforms would help accelerate the company’s “conversation-as-a-platform” strategy and boost adoption and lock-in for Microsoft’s cloud platform. If the social graph was hosted in the Azure Marketplace and offered convenient API hooks that played nicer with Microsoft’s platforms, developers would want to host their apps on Azure.

For example, a developer could build a bot that analyzes email activity (via the Microsoft Graph), as well as which employees in the company are updating their LinkedIn profiles, and then models that data with Azure Machine Learning to notify managers which of their employees are likely to churn. Of course, this raises major privacy issues that Microsoft and LinkedIn would need to address. Protecting users’ privacy is paramount for a consumer service like LinkedIn that touts “members first,” and this will get more challenging as it moves into the enterprise space.

What does intent data mean for the data-driven marketer?

This byline by Infer’s Sean Zinsmeister was originally published on Marketing Land.

Columnist Sean Zinsmeister takes a deep dive into intent data, explaining how you can use it to increase your predictive power and revenue.

As big data increasingly becomes more accessible, marketers are looking for ways to make it more scalable and actionable in order to better target prospects in various stages of the buyer journey. Intent data is synonymous with this topic, but it understandably causes a great deal of perplexity for many marketers.

It can be difficult to sift through all the terminology: It’s variously referred to as activity, behavioral, internal intent data, or external intent data. Pairing intent data with other customer signals — like those housed within a company’s marketing automation system — provides an especially unique opportunity for businesses to understand and leverage customer insights.

Nonetheless, it’s a topic that will continue to gain steam as more companies look for new ways to identify and predict where customers are in their buying journey.

Defining intent data and its uses

To start, it’s helpful to define common terms for a clear understanding of the various types of intent data out there, and how they can be applied. Simply put, intent data is information collected about a person’s or company’s activity. For the most part, it falls in one of two main categories, each of which best serves a different purpose:

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Druva Chooses Infer to Predict Highest Potential Prospects

We’re always happy to welcome another customer to the Infer family. Like many of our customers, Druva has grown rapidly in recent years and needed a better way to evaluate and prioritize good prospects for personalized follow up. The company chose Infer Predictive Scoring to take the guesswork out of the equation and better predict its highest converting leads.

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In a recent conversation Melissa Davies — who is in the process of implementing Infer Predictive Scoring at Druva — shared her adoption tips learned from building successful predictive programs over the years, why she chose Infer, and her goals for predictive at Druva.

Melissa, you’re no stranger to predictive. What are your best practices for driving adoption?

Before rolling out a predictive initiative across the entire organization, I recommend first running a controlled pilot program with a few sales reps. By piloting predictive scoring with a small group, you can build trust, create internal champions, test your use cases and strategy, and then optimize as needed. Once the approach has been perfected and you’ve shown its potential impact, it becomes easy to scale predictive across across sales and marketing, quickly gain alignment and buy-in, and ensure consistent adoption.

You’ve worked with several predictive vendors over the years. What made you choose Infer when you joined Druva?

I chose Infer over other predictive vendors because of its high quality data and open platform, which ensures I’m able to leverage all of my prospect data to recognize the full potential of our top prospects. Infer is now an integral part of our sales and marketing stack, and will help Druva become a fully data-driven organization powered by predictive insights.  

What immediate benefits do you expect to see once Predictive Scoring is in place?

Within the first month of implementation, I expect a ten percent increase in meetings booked with more qualified prospects, and with less time and energy spent getting there. Infer will also help us programmatically evaluate the quality of purchased leads upfront so the team can focus time, energy and marketing spend towards the list vendors and prospects that will make the biggest impact on revenue.

Download the full snapshot to learn more about how Druva plans to utilize Infer Predictive Scoring to drive revenue and build sales and marketing alignment.

 

 

Predictive Analytics for B2B Sales and Marketing has Certainly “Crossed the Chasm”

This Q&A with Infer’s Sean Zinsmeister was originally published on MarTech Advisor.i1916_575e6510c2543

Predictive analytics for B2B sales and marketing has certainly “crossed the chasm”, but it’s still in the early adopters phase of the product development lifecycle, and will continue to mature. MarTech Advisor spoke to Infer’s Sean Zinsmeister about the predictive space and Infer’s product strategy.

Consolidation Versus Integration of Predictive Intelligence Platforms

I expect that we’ll see some consolidation, but even more integration as the industry evolves. The reality is that today’s marketing clouds are still fairly immature and cobbled together vs. providing one cohesive cloud. When you look at the predictive movement, there has been a lot of hype and a lot of vendors chasing shiny objects. Our strategy is not to build an all-in-one solution or a walled garden, but rather to deliver an open architecture that can share data, predictions, recommendations and action triggers across any marketing cloud, system of record or other specialized tool (i.e. AdRoll, Outreach, Pardot, Act-On, etc.).

Open architecture is especially important because martech is getting increasingly balkanized by salestech, and the go-to-market stack is expanding. Our approach is to build deeper hooks into engagement systems. This will in turn increase the predictive power of our models and allow us to drive more targeted segmentation, recommend appropriate next-best actions, and ultimately make all of a company’s systems run more efficiently.