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How AI And Machine Learning Can Make Forecasting Intelligent

Geoff Birnes AtriumTraditionally, CRM solutions have been unreliable for sales forecasting. Companies have dealt with inaccuracies and blamed their bad data. However, things are starting to change thanks to artificial intelligence (AI), machine learning (ML) and predictive analytics. According to Salesforce, only a quarter of companies use predictive analytics. Of those using it, 86% have already seen a positive return. Predictive analytics can be brought to the CRM to create more accurate sales forecasts and provide actionable insights for reps, partners and managers.

ABM’s Potential Is Endless. But We’re Already Endangering It

Screen Shot 2019 07 12 at 5.29.44 PMWe’ve all seen the buzzwords in recent years. Big Data. Artificial Intelligence. Smart everything, from toilets to thermostats. Companies rush to keep up with the next fad without really understanding what the true advantages of this new technology are and how it can impact their business. The actual technology becomes overshadowed by the hype, unable to deliver on the many promises that businesses rush to peddle.

Intent Signals: Which Ones Are Truly Actionable?

Jeff KostermansRemember “predictive analytics” — now more commonly referred to in B2B marketing and sales circles as “intent?” Well, that space has matured, and today there are more than a handful of companies touting intent capabilities. But not all intent is actually intentional when it comes to real interest in your solution.

Sizmek To Acquire Rocket Fuel

1aRocketFuelSizmek, a people-based optimization and data activation platform, has entered an agreement to acquire predictive marketing platform Rocket Fuel. Under the terms of the merger agreement, an affiliate of Sizmek will buy all of the outstanding shares of Rocket Fuel’s common stock for $2.60 per share in cash—representing approximately $145 million enterprise value for Rocket Fuel.

3 Reasons Predictive Can Help Boost Marketing Intelligence

Shari.Johnston 1Talk to any marketer today and he or she will tell you the same thing: “We need better insights into our marketing engine.” In the age of AI, machine learning, and all things marketing intelligence, I often find that most conversations center around data quality. As a marketer, I find that it’s easy to put the impetus on better marketing intelligence.

6 Steps To Optimize Your Contact Data For ABM

Brian hession 1croppedWhether you have embarked on an ABM program or are planning to do so, you’ll realize that contact data issues are amplified with an account-based approach. With the spotlight on your that data, there is nowhere to hide. Sales and marketing will blitz your contact data, so now you need to worry about a lot more than just email deliverability. 

Think about it—you have a lot riding on these high-profile accounts, and the last thing you need is inaccurate, incomplete, or missing contacts holding you back. To ensure your efforts yield positive results, follow this six-step process to ensure your contact data is ready. 

Step 1: Identify Your Target Accounts

There are a number of different approaches that sales and marketing take to establish target accounts. A common one is based on firmographic criteria (i.e. company size and industry) and often supplemented with additional attributes, such as technology installs or buyer intent data. More advanced approaches include predictive analytics, which utilizes data and pattern recognition to identify the accounts with the highest propensity to buy. 

Step 2: Take Inventory Of Your Contacts

With the accounts identified, it’s time to pull together and assess all the contacts you have associated with these companies. No matter the number of contacts you have, are you confident they’re accurate? How are you going to deal with fractional records, like ones missing job title, phone numbers or email addresses? To get a handle on the state of your contact data, start with a Data Health Check. Most data providers or agencies offer them at no charge.

Step 3: Cleanse Your Contact Records

With insight from the health check, you can now strategically clean-up your contact data. First, consider suppressing contacts that are misaligned to your audience definition. It makes no sense to invest resources and time on contacts that play no role in the buying process. Second, apply real-time hygiene to the eligible contacts to isolate bad and problematic data. Lastly, fill in missing fields and enrich with attributes that provide a more complete view of the contact. 

Step 4: Understand The Size Of The Addressable Market

Now that your data is clean and complete, you need to map the buying committee—including decision makers, influencers, and end-users—within each account. With a contact gap analysis, you’ll learn the extent to which your house contacts align to your audience definition, and you’ll gain insight into the ones that you’re currently missing.

Step 5: Design A Contact Acquisition Strategy

With an understanding of the gaps within your database, you can design a contact discovery strategy to close the most important gaps first. The objective is to identify and acquire the contacts that constitute the buying committee within each account.

Step 6: Implement A Continual Contact Data Strategy

To increase ABM success, it’s imperative that your contact data management strategy is ongoing. You need to maintain a standard of accuracy with your house contacts while simultaneously seeking greenfield contacts as they become available.   

Optimizing your contact data for account-based marketing is a process that requires continual attention. You can gain a competitive advantage if you can improve the accuracy and completeness of your contact data while simultaneously ensuring you have identified the right people at each account. It’s this idea of establishing the buying committee that provides you the foundation to orchestrate plays that will build brand equity and revenue. Check out this brief video to learn more: 

Brian Hession is the President & Founder of Oceanos, where he helps companies design data management strategies that deliver smarter data, better marketing automation performance and more revenue.  Brian is a member of MOCCA Operations Board—the leading professional association dedicated to operational excellence in marketing operations—serving as Data & Information advisor.

Why Infusionsoft Evolved To Predictive 2.0

Doug Sechrist 1As a B2B marketer, my mission is to drive revenue.

This mission is one that I’ve been privileged to take on time and time again to multiply the customer base at several of the top enterprise software companies on this planet. From early days at Eloqua to Five9 and now Infusionsoft, the pipeline and leadership expectations for the marketing team has always been huge, requiring a vision and team that will hopefully act as a precedent for other marketers faced with aggressive goals. While I’ve had some early wins and lessons learned – I am now tackling the steepest challenge of my career as the VP Demand Marketing at Infusionsoft.

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