Traditionally, business-to-business (B2B) marketers used marketing automation in a similar fashion as consumer marketers. Dashboards, lists, and workflows were built to help companies interact with a collection of single-contact files, regardless of whether or not these contacts were part of the same client account. Salesforce's newest creation, Einstein Account-Based Marketing (ABM), wants to change all that.
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Built with an account-focused approach, ABM seeks to automate the work done between sales and marketing teams to identify target accounts, marry data between sales and marketing databases, and execute campaigns to each account's primary decision maker. Think of ABM as a mutation of Einstein artificial intelligence (AI), Salesforce customer relationship management (CRM), and Salesforce Pardot marketing automation—except everything is geared toward prospect groups rather than individual prospects.
"B2B marketers have tight budgets and want to focus on customers that are most likely to buy, so they've shifted to account-based marketing," said Michael Kostow, Senior Vice President and General Manager of Salesforce Pardot. "But account-based marketing is very difficult to do at scale. There are multiple influencers who are part of the buying process, and you've got to market to them with personalized content across sales and marketing channels."
However, because sales and marketing tools are traditionally separate entities that may or may not integrate with one another, Kostow said the process of identifying these group targets and pushing them through the prospect, lead, buyer, resell, and upsell process has been difficult.
Here's how it works: The tool's AI identifies key accounts by using historical interaction data. Lead scores increase or decrease as the AI identifies positive or negative interactions. Salesforce's Advertising Studio, which is also built into the ABM tool, then pulls in CRM and interaction data to help identify similar accounts. The AI will also continually scan for engagements to find opportunities when it is optimal for marketers and sales staff to send messages. It also scans account interactions to determine if deals that are already in process are progressing in a healthy way or if extra attention is required.
For example, Einstein will scan email interactions with your contact to pick up on phrases such as, "Ask my boss" or "Run that up the chain of command" to let you know if you're speaking to the decision maker. If Einstein sees these phrases, then it will alert you to the possibility that you're not pitching to the right person in the account. Additionally, if someone in an account engages with a specific piece of content or if they make a purchase that will require a secondary purchase, then the tool's AI will trigger an alert.
ABM's dashboards are entirely account-focused, which better lets sales and marketing staff determine the success of campaigns based on how groups of B2B buyers relate to content. For example, marketers can identify the attributes of marketing campaigns that have the highest potential to drive sales for targeted accounts by determining that a sequence of clicking on an ad, downloading an ebook, and watching a webinar is the optimal journey for converting prospects into high-quality leads, according to a Salesforce statement. You can then monitor this type of campaign against different campaign types to determine which approach will be more successful in the future.
ABM clients include job search website CareerBuilder, chemical products company Sika Corporation, and business consultancy Slalom. To get the full Einstein ABM experience, you'll have to combine several Salesforce modules (and pony up a hefty amount of cash in the process). The modules you'll need are:
- Einstein Account Insights, Einstein Lead Scoring, and Einstein Opportunity Insights (all part of Sales Cloud Einstein), which costs $50 per user per month,
- B2B Marketing Analytics, which costs $300 per month,
- Sales Analytics, which costs $75 per user per month,
- Engagement Studio (part of the Salesforce Pardot B2B Marketing edition), which costs $1,000 per organization per month,
- Salesforce Engage, which is an additional $50 per user per month with any Salesforce Pardot edition,
- Advertising Studio, which costs $2,000 per organization per month.
So, you're looking at a minimum $3,475 monthly expense if you decide to go all-in. However, because of this modular approach, you can build your own system based on the specific services you'll need and the price you're willing to pay.
Announced in September 2016, Einstein AI takes advantage of Salesforce's deep learning, machine learning (ML), predictive analytics, natural language processing, and image processing tech to serve as a robotic account manager. Einstein is capable of processing billions of data points, repetitions, and images to help you improve your workflow. The tool is flexible and intelligent enough to let you program specific automation and prediction outside of the standard use cases. Einstein learns from your usage to recommend improved workflows that are specific to your organization.
All Salesforce customers gain access to Einstein regardless of application or price tier. So, if you're only using Salesforce as your helpdesk software, then you'll still be able to leverage AI to improve service processes. However, the more data you tie into Salesforce, the more helpful Einstein will be. Einstein's application programming interfaces (APIs) can be plugged in beyond the Salesforce suite itself to connect to third-party apps and websites. This lets you pull data from your own e-commerce website or your corporate email account to help Einstein make more intelligent recommendations.
Of course, Salesforce isn't the only CRM and marketing automation player taking advantage of AI. Zoho recently added an AI-based virtual assistant to its Zoho CRM tool. The new feature, Zoho Intelligent Assistant (Zia), is an automation engine designed to deliver unprompted, data-based recommendations to sales staff whenever they are using Zoho CRM. Limited to Zoho CRM, Zia is engineered to detect system usage anomalies, suggest optimal workflows and macros, and advise salespeople on when to contact a prospect, according to Zoho Chief Evangelist Raju Vegesna. There's IBM Watson Analytics, the granddaddy of ML and AI. Watson is primarily a business intelligence (BI) tool but it's also a virtual agent, an e-commerce tool, a marketing solution, and a game show contestant.