Account-based marketing (ABM) software realigns marketing and sales departments away from general branding and lead generation strategies by identifying quality target accounts prior to implementing a tailored marketing strategy. ABM software offers tools to automate and reduce the lengthy process of identifying prospects and dedicating the right resources to nurture the most promising accounts. ABM software enables users to generate highly qualified leads, craft personalized buying journeys, increase customer lifetime value, and build further opportunity for in-pipeline accounts. ABM allows users to combine prospect data with real-time customer experience technologies to facilitate an account-based marketing strategy. This enables organizations to align marketing and sales teams toward the company’s goals. ABM software can be used to acquire new accounts, nurture existing and promising accounts, and expand and grow enterprise accounts. Some ABM products can integrate with third-party sales and marketing applications, such as marketing automation platforms and customer relationship management (CRM) software, to better target and prioritize communications with key accounts.
A quality account-based marketing strategy requires intelligence gathering, continuous sales-marketing communication, and general organization-wide awareness of target accounts and ongoing sales cycles. Salespeople making contacts and marketers receiving leads need to know quickly whether this account is already in talks for a deal as well as the results of any investigation by sales or marketing into whether the account is a good fit for their products. Account management systems serve to document and communicate this information between departments. These systems (1) automate the transfer of important account information between contacts and their linked accounts, (2) communicate account-level details between sales and marketing, and (3) manage marketing funnels or sales pipelines at the account level.
Account management systems tend to integrate with sales or marketing automation systems and maintain account information in those databases, but some can also serve as a standalone system of record. In a simple sense, the “how” of account management is just adding the account record as an object to be documented to (a record that exists already in many CRM systems). The value of account management derives from greater administrative control over where account information comes from, how it updates other parts of the system, and management of duplicates or missing account information.
For example, a lead from an existing account may enter a system with its own firmographic information (like if the lead selected their company size on a form). If this contradicts the existing account information, how does the system handle the incongruity? Which is considered the master record? And, what notifications or workflows does this change of information initiate?
Account management systems also provide tools to make sales or marketing automation systems more account-centric, such as:
Account management systems should be evaluated based on their alignment with marketing’s ABM strategy. Sketch out how account data is being acquired, what records it needs to update, what data needs to be recorded, who needs to see it, and which other systems it needs to flow to. An account management product must support your organization’s workflow and strategy.
Account-based marketing substitutes a traditional wide-top funnel with a narrower and more focused marketing funnel. Accounts need to be qualified before they become leads, and this requires data. Account intelligence products (1) connect existing leads in a marketing database to their account and provide qualifying data about that company and (2) connect marketers to prospective accounts based on their ideal account persona. They may also (3) implement a lead scoring engine to better qualify leads and optimize a marketer’s target account list.
Sales Intelligence platforms traditionally focus on data like contact information and company personnel hierarchy. Account intelligence expands this focus to:
Intelligence platforms are often plagued with stale, missing, or irrelevant data. As a cure, account intelligence platforms have begun relying more on feeds of automatically updated account data. The variety of data provided differs greatly between platforms but can include media mentions, social media sentiment, website domain analysis, and employee web and search engine activity. Account intelligence platforms can deliver this data wholesale or utilize it to interpret buying signals, such as notifying marketers when a target account receives a sizable investment or an account’s employees are researching products similar to their own.
Because of this shift toward big marketing data, marketers are now burdened with industry noise instead of interpretable buying signals. To make platforms more useful, some vendors have developed lead scoring or lead qualifying systems to guide marketers to their ideal accounts. A lead scoring or account scoring engine may evaluate accounts using:
Ideally, lead scoring both qualifies existing leads (to determine their match to a product portfolio and an ideal client persona) as well as delivers new qualified accounts that are exhibiting buying behavior.
Account intelligence platforms should be evaluated on these criteria:
When negotiating complex or expensive sales, a buyer receives input and approval from a number of stakeholders in their organization—many of which a sales team may never come in contact with. Account-based ad targeting is designed to sell to everyone involved in the buying process, even those that sales never speaks with. By placing highly targeted and highly personalized advertising stock, marketers can influence buying decisions and build brand awareness in a company at low cost (very few impressions), even before sales reaches out. Account-based ad targeting (1) segments audiences by account and (2) serves ads on an account-by-account basis.
Account-based advertising segments audiences by serving ads to:
The system typically provides a database of known IP addresses, while additional addresses can also be obtained from certain website visitors or an email exchange. Website visitors receive cookies when landing on your page, which can catch account stakeholders working from other locations. These systems then integrate with ad exchanges or provide demand-side platforms (DSPs) with the ability to place ads in front of the leads that marketers have already qualified. Any channel including mobile, social, search, display, and video advertising that account contacts encounter during their workday can carry brand messaging.
Account-based advertising platforms should be evaluated on these criteria:
An effective account-based marketing strategy often entails crafting tailor-made buying journeys for each account or for each account persona. Each account contact that encounters the brand needs to be served content in line with the buying proposition that sales and marketing have developed. This can be done with personalized proposals and on-going sales conversations, but (as discussed in regard to advertising) decision makers that sales never speak with are also researching your product independently. Account-based personalization delivers web experiences to visitors specifically designed for them based on their associated account.
Web personalization software evolved out of A/B testing platforms used to optimize websites. A/B testing platforms deliver different web experiences to randomly selected visitors. Combining A/B testing’s traffic bifurcation capabilities with real-time audience segmentation allows web or mobile experiences personalized to individual visitor needs. For account-based personalization, the real-time data is the same account IP address and retargeting cookies discussed in the advertising section. When a predetermined IP address or a cookied browser accesses a site, account-based personalization software deploys a custom page designed particularly for that sale.
Account-based personalization platforms should be evaluated on these criteria: