How to Maximize Marketing Automation Impact
The understanding of marketing automation (MA) is fragmented due to its origins, evolution, diverse platforms, and wide range of use and misuse. By researching, selecting, and implementing functionality aligned with strategic goals, brands can accelerate progress toward their goals.
- What is Marketing Automation?
- Can Marketing Automation . . . ?
- Approaches to Marketing Automation
- Marketing Automation Standard Components
- Marketing Automation Use Cases
- Choosing a Marketing Automation Platform
What is Marketing Automation?
Over the last 25 years since marketing automation (MA) was introduced, one constant has been the platform’s variation: in functionality, user application, and general understanding. While the majority of businesses have adopted some form of marketing automation, the general fragmented understanding of the platform has led to misaligned implementation choices and mixed results.
Marketing Automation Defined
Marketing automation is any set of generally recognized functionalities that automate, expedite, and optimize marketing tasks at a scale that, in many cases, would otherwise be cumbersome or impossible.
At its best, MA combines existing customer data from the business’ CDP/CRM, additional real-time critical customer data (traditional and behavioral), analyzes it, and facilitates actions (segmentation, scoring, personalization, workflows, multi-format messaging) tailoring elements of the customer experience and journey to boost marketing and sales success.
How Marketing Automation Challenges Simple Definition
Marketing automation vendors came from a wide range of starting points, beginning as software support embedded in a particular industry, an early CRM provider who began adding marketing functionality, or even a start-up begun by ex-employees of earlier business software firms with an expressed intention to build a marketing platform.
Early MA was typically used in concert with a CRM, either previously installed by the business or packaged together by the vendor. Now MA platforms often have their own CRM functionality, while CRMs have MA functionality (or at least an add-on to a proprietary CRM).
Vendors carved out their niche: email automation, lead scoring, all-in-one CRM/MA tools, best for small business, best add-on for CRM Brand X. Consequently, the vendor landing pages, display advertising, and content marketing naturally reflect a specific definition of marketing automation that aligns a customer need with the vendor solution.
The explosion of marketing in the past decade–and what the term “marketing” now encompasses–has changed the role of marketing for business and for the customer. Consumer expectation, and competition in general, requires that marketing play a much more visible, strategic role throughout the organization. When channels expanded, opportunities for marketing strategy and tactics multiplied along with the digital ecosystem. As the definition of marketing grew, so too, marketing automation expanded. In this new unfrozen moment, no constraining guardrails existed beyond, “Does this help a marketing goal in a specific situation?” As a result, the boundaries of what was possible in marketing (and automation) were few.
This broad spectrum of platform functionality created corresponding definitions and purposes, along with documented positive, if decontextualized, results. As a result, some businesses adopted without a clear goal and strategy and experienced results that fell short of expectations.
”Be able to articulate the main benefit that your organization wants to get from marketing automation”
–Claire Wood, Marketing Director Deloitte
Fortunately, marketers with clearly planned goals can select platforms and functionalities they need from a wide range of effective toolsets through critically reading reviews from industry publications and vendors alike.
Marketing Automation Evolution
When Marketing Automation (MA) appeared in the martech landscape over 25 years ago, it was an outgrowth of another landmark in business technology, Customer Relationship Management, or CRM only 10 years earlier. Like CRM platforms, initial MA tools were expensive, limited, and narrowly focused. Since then, changes in industry and environment converged to reverse these characteristics, enabling MA to be more affordable, unlimited, and focused on anything under the marketing umbrella.
- Competitive new platforms joined when the software space became popular and lucrative, broadening functionality approaches and decreasing costs.
- The widespread popularity of social media and mobile devices expanded the number of effective marketing channels, creating demand for tools that addressed new opportunities.
- Software as a service (SaaS) was introduced, lowering the entry cost for platform adoption.
- High-speed internet became widespread, contributing to the feasibility of the SaaS and cloud-suite model.
- Consolidation of the market between 2010-2014 ($5.5B in acquisitions) allowed market leaders to expand functionality under single products, popularizing more comprehensive sets of features, and creating targets for competitors.
Platform Core Functionality
Today Marketing Automation is found in major platforms integrated into cloud suites managing the entire customer lifecycle, dozens of mid-tier players offering robust solutions, and hundreds of specialized applications performing different parts of MA functionality. While platforms today may vary widely in some unique functionalities or in their implementations of standard functionalities, most MA platforms support the core functional areas:
- Lead Management: automating lead generation (lead capture), scoring and grading, segmentation, multi-touch lead nurturing, and workflows
- Cross-channel Campaign Management: automated email marketing, social media marketing, website marketing, listening and tracking, content creation, and testing
- Workflow Automation: automated workflows, internally and externally focused, both templated and customized, applied to lead generation and nurturing, segmentation, engagement, and retention
- Personalization and Engagement: segmentation by traditional, behavioral, and journey stage indicators; tailored messaging and content recommendation, monitoring for omnichannel responses, and rapid personalized responses
- Analytics: data capture and analysis, social media analytics, website analytics, email marketing analytics; multi-touch attribution and closed-loop reporting
Can Marketing Automation . . . ?
A typical marketing automation commitment, even with a “trial period” for a small team can be significant: Getting team members prepared, restructuring and revamping processes, tracking progress, and quantifying results. As a result, brands should ask top questions to better understand how the platform translates to success for them. Below are three common question areas often associated with MA.
Can MA Save Time Automating Manual Processes?
Yes. Some tasks are made for automating: repetitive, time-consuming, with simple enough decision logic that basic automating rules (conditions, paths, triggers, actions) will cover them. And with high-volume tasks, automation eliminates typical human error even when outpacing human speed ten-fold.
What are the best tasks to automate? Posting (and reposting) to social media, sending welcome emails for new prospect visits or downloads, confirmation emails to customers. These high-volume, simple actions may be an obvious choice. However, today’s robust MA tools automate more complex processes that would require as much or more resource time as manually posting cross-channel messages.
Scoring and Grading Automation
For example, scoring and grading leads at high volume would be an onerous process of comparing huge sets of attributes, matching, and calculating scores based on a static scorecard. Lead scoring and grading introduce subjectivity with human evaluation, likely slowing down the process and potentially presenting inconsistencies detrimental to accurately qualifying leads. Automating the scoring process, based on actual behavioral data, allows unlimited real-time processing of prospects beyond the capabilities of human responders.
Modern audience segmentation can be as complex as the brand’s targeting strategy desires. Segmentation can include any applicable audience dimension (demographic, geographic, etc.), or combinations of specific dimension qualities (existing customers, no purchases in prior 90 days; new prospect, downloaded at least one content object in the last 30 days, user of competitor product). Segmentation data is often backed by trackable (and thus, automated) data, whether demographic, behavioral, or other attributes. Manually segmenting hundreds or more visitors based on unique criteria combinations could be time-consuming, costly, and error-prone. Automated segmentation is executed in real-time.
Can ROI of Automation be Quantified?
Many platforms can calculate the return from individual programs, lead sources, or other slices of data. But quantifying a sub-function is not quite as clean. In this case, however, quantifying the ROI of automation requires comparing pre/post automation calculations. Using lead scoring and grading as an example, compare the process with a 30-day data set before and after.
|Manual Scoring Process
|Automated Scoring Process
|100 leads received/day (2100/month)Top 10 per day are selected for review using computer software manually (historically, fewer than 10 score high). Each is compared using the current brand scorecard of attributes measuring interest, the likelihood of transaction; and other attributes measuring fit with the brand.
|100 leads received/day (2100/month)All 100 are reviewed as they come in, using a scorecard augmented to measure more sophisticated and numerous attributes. Each lead is scored for interest and graded for brand fit. Result: a ten-fold increase in scoring per month.
If the financial value is to be calculated for the month, the result would resemble the formula below.
|Manual Financial Lead Value
|Automated Financial Lead Value
|[((210 leads x .35 x $800) – M cost)] 73 leads close for $60,000 gross revenue
|[((2100 leads x .170 x $800) – M cost)] 357 leads close for $285,600 gross revenue
The scored leads are multiplied by the actual conversion rate and the average sale price.
While this example does not compare the unknown marketing costs between the two approaches, it does present a method to compare lift from automation.
The conversion rate is cut in half (from 35% to 17%) when automatically scoring the full lead intake, as the expectation is that the best leads, even manually chosen, would be in the top 10/day.
Of course, the automated system would segment those leads not yet MQL, and place them in a specific nurture segment for more marketing. In both cases, the ROI of the full set of converted leads would span into the following month as late-month leads converted.
Can MA Help Align Marketing and Sales?
Yes. But it takes more than software alone to achieve. Marketing and sales often approach lead generation using different criteria, with marketing more likely to overstate the readiness level of a lead to make a transaction, and sales preferring a defined qualified lead: a prospect who meets a specific threshold of interest, decision-making authority, and a company match to the brand.
Standardization Defined by Collaboration and Data
Marketing automation can assist by standardizing the scoring thresholds for different criteria that make up a qualified lead. Automated lead scoring and grading work by assessing prospect attributes (company characteristics, demographic, psychotropic, geographic, and most importantly, behavioral) and applies points for different attributes. Lead scoring measures the prospect’s readiness to purchase, while lead grading measures the prospect’s fit for the brand.
The challenge, however, is not the automated scoring, but the scorecard definition: How much should different attributes count toward lead qualification? Brands that collaborate in defining a qualified lead are more likely to align marketing, sales, and other parts of the customer lifecycle. Sales reps can share their experience in attributes of successfully converted prospects, their behaviors, their background, interests, and other observations. For example, they might note that a prospect who watches several informational videos is less likely to buy than a prospect who downloads the white paper on specific product use.
Marketing automation acts as a catalyst to align marketing and sales, and once the scorecard is defined, functions to maintain alignment. However, the actual collaboration to achieve a shared qualified lead definition must be accomplished by pipeline stakeholders first and must be repeated when new attributes are introduced.
Can MA Increase Lead Generation?
Yes. Marketing automation platforms excel at automating many of the core tasks that generate leads, including automatically capturing all visitor interactions, creating forms for capturing additional prospect information, and tying the form data capture to behavioral data. Once a minimum data threshold is reached (as defined by the business), the prospect can be placed in an early lead workflow automatically.
Through cross-channel marketing, automated tracking, and analytics, marketing automation platforms can function as a force for generating and capturing leads at high volume.
Content Marketing for Lead Generation
One of the earliest email marketing automation models remains popular today. Once visitors have opted-in to receive emails from the brand, they are added to an initial welcome segment, triggering a welcome email with content aligned with initial interest and behavior. If clicked, visitors go to custom landing pages aligned with expressed initial interest. The prospect’s path and interactions are tracked, and subsequently “extra” content is linked in the next message. Visitors who download the additional content are then automatically re-scored and graded, then segmented into a new lead category and an appropriate workflow
Similar content marketing can occur across channels. For example, when visitors click promoted posts in social media, their data is captured and used to serve content aligned with preferences, interaction history, and additional data when opting-in for emails from the brand
Nurturing workflows ensure those leads capable of becoming qualified are not lost and can be automatically passed to the sales team with all of the relevant data to continue a personalized experience.
Because no significant limit is imposed by a high-volume of visitors or prospects, the MA platform can ensure no lead goes unnoticed, with little impact on company resources. However, this approach is dependent on available content, including continued new and updated content, to continue marketing to prospects throughout the customer journey.
Approaches to Marketing Automation
Timesaving or Strategic Insights
Each year in marketing surveys, a significant percentage of marketing automation adopters agree that the top benefit of implementing marketing automation platforms is the time savings. Other respondents point to top benefits such as new insights and business intelligence, change management, and the re-invention of marketing.
While the distance between saving time and strategic gains may seem profound, the business landscape necessarily contains one-person marketing departments for whom automation determines whether significant marketing is even possible.
While most marketers believe that investing in emerging technologies is important, most are realizing only about 50% of their installed martech’s potential.
Automating Legacy Practices
Automation alone may not succeed in aligning sales and marketing; nor will it fix a broken sales process. It will, however, speed the development and delivery of an existing email marketing campaign, increase accuracy above manual data entry, and reduce response time for prospect or customer inquiries or reminder emails.
Effectively communicating at scale is a significant advantage of marketing automation, but even that understates the potential impact of loading all current program data and parameters into a MA platform. Drip campaigns will be more profitable, multi-channel marketing with data tracking is possible, A/B testing will improve campaigns across channels, and limited personalization will be cost-effective. And while all brands would benefit from an accurate and data-driven strategy prior to implementation, using MA can help brands formulate a strategic marketing plan, guide revisions, and ensure alignment with the reality of a brand’s target market the longer it is used.
In fact, if tactical automating, streamlining, and timesaving alone were the platform’s output, a strong case could be made for adding it to a business’s martech stack (within cost limitations). The automation (and streamlining) of cumbersome processes allows a small marketing team to maximize resources, accomplishing far more than they could alone. Some tasks, such as responding to a high volume of inquiries in real-time are not feasible without automation.
Driving Strategy with Marketing Automation
Using strategic research and planning, brands have quantified the value of the market and determined tactics most likely to gain market share. Buyer personas were developed, and customer data has been captured and analyzed. Competitor market positioning has been researched, analyzing their offering attributes and digital presence in order to exploit competitive advantages and ameliorate product attributes below parity.
In short, brands that use a strategic framework and market analysis are able to define specific goals for marketing automation and implement data-backed tactics in an effective marketing mix–all refined and accelerated by aligned use of a marketing automation platform.
The brand marketing team can implement MA platform functions using researched data:
- Lead management functions are configured for optimal performance against current target segmentation and buyer personas.
- Cross-channel campaign management is planned and executed using data from competitive dimensions (digital presence, SEO, technology stack configurations, etc.)
- Customer engagement is informed by documented user paths on landing pages, page information architecture, and the customer journeys they define.
Results from MA implementation provide new data points and insights, which are then fed back into the strategic marketing plan to create ongoing optimization of all elements of the marketing engine.
Marketing Automation Standard Components
The standard functionality of marketing automation platforms encompasses most of the practices for a digital marketing group:
- Lead management
- Campaign management and optimization
- Automated workflows
- Personalization and engagement
- Analytics and reporting
Marketing automation platforms can support end-to-end, awareness to advocate, lead management. Automating components of each step, MA facilitates lead capture, scoring and grading, nurturing, and ensuring MQL before sales begin to follow up.
Since prospects come from a multitude of sources for different businesses, MA platforms include lead capturing tools spanning channels and customer journeys. Using automatically generated tracking URLs and forms, the platform captures core prospect information for visitors as they interact with the brand, and as they download materials relevant to their search (white paper or e-book, a newsletter, discount coupon).
Social media listening tools capture data required for analytics to complete sentiment analysis, answering specific questions that affect prospects at the top of the funnel (How is the brand portrayed in mentions? Is it negative or positive? Mentioned with a product?).
For websites and the email marketing that points visitors there, the volume of visitors, the number and types of resources downloaded, and their location in the customer journey are all captured without dependence on a large sales and marketing staff. As a result, no lead is passed over due to inadequate resources. Leads that may have dropped previously due to resources are now in the pool for nurturing to Marketing Qualified Leads (MQLs).
Lead Scoring and Grading
The first step in scoring and grading is similar to the approach necessary for offline models: all parties that support moving prospects from unaware to advocate collaborate and define the characteristics of what a prospect looks like at key points in the customer lifecycle. Marketing and sales alignment is a natural outcome of jointly working to define the process, combining experiences with prospects moving through the cycle, identifying indicators each recognizes as prospect behavior reaching a conceptual milestone in the customer journey.
By tracking prospects’ location in the customer journey and evaluating their level of interest and knowledge, a scoring engine assigns points to different criteria including specific behaviors and actions, which feeds into marketing strategies and tactics. Using a system of these indicators provides the Digital Body Language (DBL) that provides scoring value that can inform the brand response. Digital tracking of prospects on websites, social media, and other digital platforms is rapidly analyzed and applied as input into lead scoring, communication guidance, dynamic content, and segmentation.
Grading is also automated, as some platforms will automatically pull company data on size, structure, business model, revenue, profitability, etc, to ensure customer alignment with the brand, regardless of lead score’s measurement of interest and brand knowledge).
When leads are first captured at the top-of-funnel, they are often unqualified for sales, and they each have different educational and discovery requirements based on level of interest, product knowledge, and need. Marketing automation platforms can provide the content and customer experience to move them along the customer journey to an MQL.
The goal is to get the right content to the right people at the right time. MA tools can help businesses come closer to achieving just-in-time personalized content targeted to prospects at all phases of the journey or funnel.
Consumers today seek out information prior to purchase, and automated nurturing campaigns speak directly to the demand for product and service knowledge, with content focused on the need, providing the right type of information for a prospect at a given point in the journey.
Platforms help provide a customer experience that aligns with each prospect through lead segmentation, splitting the prospects into groups based on multiple sets of indicators (demographic, psychographic, geographic, behavioral) captured from data sources such as CDP/CRM, and during the customer journey. These groupings ensure that a prospect or customer receives relevant information that helps inform a transaction.
Cross-channel Campaign Management and Optimization
Marketing automation platforms centralize many campaign tasks needed to reach prospects and customers, using personalized and multi-format messaging across channels, creating targeted content in posts, landing pages, forms; allowing for capture, monitoring, and testing to provide the most effective communication matching the customer’s needs. When campaigns are properly set up, marketers can focus on higher-level tasks (creative design, monitoring marketing activities, aligning activities with strategic planning and market analysis) while the platform sends tailored content and messaging automatically through triggers and timers, all while capturing customer data and using it to better target customer needs.
One of the earliest and most popular functionalities in MA, automated email marketing is used for a wide variety of campaigns, including drip campaigns for nurturing, retention campaigns with upselling and cross-selling, and re-engagement campaigns for inactive customers. Email campaigns can be targeted by demographics, industry profiles, and behavior, including a customer’s interactions with the brand. Campaign actions can be automated, with messages sent in response to triggers, a set schedule, or even a delay. The MA platform tracks email delivery, email open, and different responses to the campaign message. When a customer clicks through emailed content to a website, all online actions are tracked and used for further segmenting and scoring. This additional customer data allows the campaign to continue tailoring the message as the customer’s need changes.
Social Media Marketing
With multiple social media platforms now in widespread use, the ability to centrally manage campaigns across multiple social platforms allows marketers to schedule automated posts across platforms, automate replies to customer inquiries, and ensure an ongoing presence without significant resource commitments. MA platforms typically support measuring brand mentions competitively and provide listening tools for brand feedback to understand the perspectives of prospects and customers, all of which can drive changes to MA strategy to raise the social profile of the brand. Finally, the MA platform can be used to manage social media advertising campaigns.
Over the last decade, businesses have adopted a multichannel sales and marketing approach to match consumers’ use of online platforms as a primary method of learning about products and services. As the number of channels multiplied and gained widespread use, the MA platforms began expanding to offer broader functionality to allow businesses to effectively compete across channels without using a separate toolset per channel. MA was able to automate a large part of the customer experience across channels; as a result, even small sales and marketing teams were capable of delivering personalized experiences across large audiences. With omnichannel marketing, messages can be automated and sent as emails, text messages, social media posts. Optimizing across channels allows the brand to send the right message, to the right person, at the right time that is most effective for a specific channel. Moreover, all the data from multi-channel touchpoints feeds back into individual marketing efforts to more effectively communicate to customers. The result of automated omnichannel meets the goal of brand and customer: a seamless brand experience as consumers navigate across channels while maintaining high expectations for the experience interacting with the brand.
MA provides templates and frameworks for creating trackable landing pages and forms, email text for automated email campaigns and auto-responses, guidance on SEO for public posts, and typically provides support to help marketers design the right content for the right target. By using landing pages with automatic tracking code, once a visitor completes a form on the brand site, the prior touchpoints are connected with the identified visitor.
Visual form builders make creating progressive profiling forms simple, allowing visitors to input little information across multiple visits, and can even pre-populate some information if the brand’s CRM/CDP is integrated with the MA platform. Finally, marketing automation can help SEO efforts, which in turn drives traffic to brand content. Many MA platforms help marketers optimize landing pages and content through templated guides. Templated approaches also drive customers to provide product and service reviews, which also raises the brand’s authority and relevance.
Marketers spend significant time monitoring campaign early returns to verify all parts of a multi-channel or multi-format program are functioning as expected and delivering results, looking for opportunities to improve early in the launch. Using the built-in testing of a marketing automation platform allows the brand to A/B test variations of specific components prior to full launch. Most commonly, landing pages, email subject headers, and forms can reveal significant response variation based on layout, prominent text, and even send times in email campaigns. Location of call-to-actions, paragraph vs bulleted text, and the navigation buttons are quick to test with a MA platform and can have a measurable impact on responses. Even swapping the image in a social media post can increase responses 3-fold.
An automated workflow is a rules-based set of user actions that use simple operators (triggers, conditions, delays, actions) to create paths of action and decisions that accomplish a marketing-related task. Most workflows save time and achieve real-time, rapid tasks difficult to achieve manually. Automated workflows can capture lead information, segment visitors or leads, and automatically send specific messages based on defined criteria on a predetermined schedule.
Workflows are driven by combinations of these operators to create the rules for each workflow.
- Trigger: a defined event that starts a specified action, for example, someone completing a registration form is a trigger, and the action resulting can be a welcome email confirming registration.
- If/Then Conditions: decision action based upon the state of the object in question (if X is true, then do Y). Conditions are often part of workflows for segmenting: If the page visited was <products> then place on <products> list
- Delays: sets a time duration between steps in a workflow. Commonly used to pause actions to send reminders, e.g., after receiving software setup instructions, wait 30 days before sending a reminder.
- Actions: defined action to occur from a trigger, or if a condition matches.
The number of workflow possibilities is virtually endless, but marketing automation workflows typically align with these types:
- Lead generation
- Lead nurturing
- Customer engagement
- Customer retention.
Guided and visual workflow builders simplify a normally complex process of multi-touch, cross-channel, and cross-functional workflows. The need for a rapid succession of actions (e.g., high volume of personalized follow-ups after an unqualified prospect inquiry) would be problematic manually. Other more complex automated workflows will use multiple conditions to capture a lead and nurture it, responding to behaviors throughout: Incentivize readers to opt-in to receive targeted information, deliver information, adjust information content or velocity.
Personalization and Engagement
Expectations of personalized brand interaction have grown substantially over the last decade, and technology-enabled companies have responded by ramping up to meet and confirm expectations. Most consumers expect businesses to understand their needs, and many consider a non-personal experience a reason to shop elsewhere. When done well, personalization is favored by the business and consumer: the brand needs more personal data to better target buyers of a product or service; customers expect the brand to know what they need. In 2018, Accenture’s survey of 8,000 consumers stated that 91% are more likely to shop with brands that provide a level of personalization. Today, the brand experience is part of the value proposition.
One of the fastest ways to achieve a degree of personalization at a large volume is through target segmentation. Whether pulling from the brand’s existing CRM/CDP, or from in-stream data, segmentation needs definition and a focus on customer characteristics that are relevant to the brand. Segmentation factors include customer behavior (Behavioral), personal interests (Psychographic), purchases (including frequency, revenue, choices), as well demographic and geographic data, a prospect’s location in the consumer journey, and even the lead score. Behavioral segmentation–focusing on a customer’s behavior when interacting with the business–is immediately relevant to the brand, as the data is actionable for marketers, and for triggers and conditions in marketing automation workflows
Digital interactions on computers or mobile devices can establish or update visitors’ interest in a specific product, the interest level in a product, and the knowledge level about the brand. Automated workflows can easily segment visitors into the appropriate follow-up workflow for nurturing.
Radius around a certain location
Urban or rural
These individual characteristics are used in combinations to identify the appropriate level of brand interaction, type of content, and even focus of the content. Creating a segment that includes (interest in product Y + leads with the highest score in the past 30 days) would likely be a Marketing Qualified Lead (MQL) ready for Sales.
Digital marketing can take advantage of customer data not only by segmenting into the appropriate group, and therefore, workflow; it can also use the data to create dynamic content in real-time. In email marketing, instead of merely placing a customer’s name at the top, the content can reflect the consumer’s demographics (geographical area, occupation), preferences set during the welcome (interests, categories of products, etc.), and even prior email clicks (content that matches format/emotion of clicked content). This dynamic customized content can be an image, a theme, or even a custom call-to-action (CTA). Dynamic content, or any personalization, should be part of a strategy, and not a careless pull of something from the database. By tracking standard and personalized content, marketers can test and compare the results of dynamic content.
Analytics and Reporting
While much depends on the various tools and utilities that comprise the integrated marketing automation platform today, few are as critical as the analytic engine that drives personalization, segmentation, lead scoring, and campaign management. Analytics creates the initial segmentation that allows a prospect to drop into the most relevant workflow. It measures the sentiment of brand mentions in social media platforms, identifying the best place to post for maximum impact. It allows marketers to tailor content to groups and individuals, and get that content to the right person at the right time.
Marketing automation provides a built-in tracking code for landing pages, or any page of the website to track click-throughs from email marketing campaigns, to follow the customer journey as visitors navigate, and track downloads, forms, and registrations. Connecting Google Analytics, or another web analytic platform provides even greater data, with detailed traffic analysis and goals/conversions.
Access to cross-platform social media analytics ensures brands get a complete view of the landscape, how branded posts are received, how brand mentions are presented and received, and how brand mentions originate. Armed with this data, marketers can get insights into customer satisfaction, product perceptions, customer input back into product design. Specific campaigns can be singularly tracked to identify what resonates most with target audiences. Ad campaigns or promoted posts can click-through to a target landing page to convert on a different action depending on the product and goal. Completing Marketing Return on Investment (MROI or ROMI) for a social media campaign is easily accomplished when the platform is gathering the data across platforms.
Email marketing campaigns have long been the most popular (and profitable) campaigns. Simple to set up, easy to understand, and, with the right target, a strong return. Setting up campaigns from within a MA platform streamlines and scales, allowing one person to manage hundreds or thousands of sends using the system. With tracking automated within the campaign, marketers can see which have been delivered, opened, or clicked. Because the platform is cross-channel, the email click-through to a website is tracked as well, and all interactions throughout the website are captured and analyzed to use for future campaign design.
Today’s consumer researches brand information, comparisons, reviews, and discussions through a path of opportunity and interest, and may as easily go from a 1) friend’s social media page with a shared article linked, to a 2) shared article, to 3) Amazon to check reviews and prices, then a 4) from Google, brand website to look around and back to his 5) social media page as he is building information to lead to a decision. A week later, 6) from Google, the brand website to purchase.
Years ago, marketers were content to track the purchase on the brand site and consider that final click responsible for convincing the consumer to make the purchase. Consequently, the MROI would be based on the cost of the product webpage from which he added the product to the cart. However, with cross-channel campaign marketing, MA will track the path, capturing the customer journey and accurately revealing attribution across sites
Marketing Automation Use Cases
Eno Roasters Coffee Market (E-commerce, B2C)
Eno Roasters began a specialty coffee bean roasting e-commerce business 3 years ago, beginning with a handful of growers spread across 4 countries. With an integrated inventory system, Eno monitors green inventory, limited roasted inventory, receiving and shipping, and roasting. As a result, Eno is able to roast just before shipping directly to consumers and small coffee shops, guaranteeing freshly roasted exotic beans directly to their door.
Eno Roasters purchases directly from a number of international growers, limiting volume to what can be roasted and sold within a narrow window. The constant small volume purchases are time-consuming, creates volatile pricing and scheduling, and are ultimately inefficient and costly. If Eno’s can increase market share, the brand would be able to contract more exclusive deals at higher volume, streamline buying, significantly reducing costs, and increasing revenue and profit.
Eno’s leadership team knew they needed to reach more prospects, increase repeat customers and “Roaster Club” subscribers, and understand their customers better in order to engage them.
Eno’s leadership team reviewed their customer and competitor data and implemented a marketing automation platform to centralize all of their marketing efforts.
Eno’s implemented a mid-tier marketing automation platform with features that aligned with their customer engagement and lead generation plans: extensive content marketing features across channels, pre-built workflows for cart abandonment and timed reminders for ordering, landing page templates, social media listening and analytics, and tools to convert existing blog sites to track with the platform.
Eno hired contractors to quickly add to a content inventory, the 3-person marketing team began setting up cross-channel campaigns, including expanding their email and website marketing, creating their first Facebook and Twitter “planned” campaigns and tagged all current and former customers by location, purchase history, single order vs coffee club subscription.
When launched 45 days later, they began with a newsletter to every customer customized by segment.
- Non-subscribers were provided with content on the benefits of subscribing to roasting on a schedule with a limited time discount. The email linked to a custom landing page, and Eno tracked deliverable, open, click-through, and page navigation, and conversion.
- All customers were grouped into 5 geographical types, and the background images in the emailed newsletter were aligned with each type (e.g., coastal, southern, northern, rural, urban).
- Dormant customers (90+ days since last purchase) received a “Re-welcoming” email, asking for feedback with a link to a short survey, and an opportunity for a discount on the next order (after completing a survey), or a reduced rate subscription.
Social media listening began immediately upon implementation, but with a historically low activity presence, actionable data wasn’t available for 30 days. With a combination of ads (photos and video) and promoted posts, Eno Roasters began to see brand mentionings increase until reaching over 300% in 30 days after increased posting and advertising, with 85% positivity.
The marketing team used a combination of templated solutions from the platform along with custom-designed marketing tactics based on existing data and analysis. Eno Roasters used segmenting recommendations, workflows for cart abandonment, order reminders, and auto-nurturing. The team used advertising in conjunction with platform features to help get the tailored message to each key segment and planned and produced content prioritized by customer interests and interaction behavior with the company blog and product website.
After 90 days, the leadership and marketing teams reviewed all the data: traffic by channel, revenue by channel, cart abandonment rates, revenue by segment, CTR by each email marketing strategy. Overall, the results were positive: Paid traffic over 200% up, and organic traffic up over 250%. Revenue was up 150%. Each component that wasn’t performing was paused or modified–low-performing segments, campaigns, specific email messages.
After 6 months of continued tweaks to segments and messaging, all metrics had stabilized above the initial 90-day checkpoint, and Eno Roasters negotiated their first large volume, long-term grower contract.
ArtSync Furniture (Pre-fab. and Custom Manufacturing, B2B)
ArtSynch Furniture offers functional and aesthetic furniture for professional studios in government, education, large businesses, and ad agencies. ArtSync is known for cost-effective rapid manufacturing and distribution channels spanning the contiguous United States. Currently offers two product lines: Load-Ready, and Built-to-Please, a fully customizable suite of studio furniture.
ArtSync began 12 years ago in one channel (traditional art studio) and crept into others (educational studio, government). Now that the original channel is barely profitable, ArtSync needs to increase growth in the additional channels, but a misalignment in marketing, communication, and sales with the channels is impeding growth and viability.
After ArtSync leadership team met with each sales representative and marketing team member, it appeared that the general problem was a lack of organization and discipline across marketing and sales. The leadership team was aware that a great many B2B brands had adopted marketing automation to drive their marketing strategy and tactics. After reading the documented ROI from a platform capable of aligning marketing and sales, they decided to adopt marketing automation.
The Solution and Results
While the implementation of a small business-oriented MA platform went smoothly, little afterward did. While relying on existing web content, ArtSync modified workflows and launched lead generation and nurturing initiatives. Tracking was added to all content pages, new forms were added, and the marketing team inputs their scorecard metrics into the automated lead scoring engine. Workflows were set up to align with the 3 channels: government buyers, educational institution buyers, and business/agency buyers. While the leadership team knew it would take time for results to grow, they were shocked when, after 60 days, sales plummeted further.
ArtSync management concluded that the platform was implemented incorrectly and hired a recommended MA consultant to assess the situation. The findings were unexpected but explained their failure to expand across channels successfully.
- ArtSync’s channel segmentation was based on superficial differences based on email addresses (ending in .edu or .gov or similar), content selection (clicking on an article that shows their furniture in a classroom, business, or government office), or self-select on web forms.
- Experiences were not tailored to channel audiences’ needs or expectations, but only to high-level differences between the target segments (content images were the main differentiator between segment treatment; brief coverage of end-user examples such as students, agency creatives, compliance-minded government art directors).
- Underpinning it all, little institutional knowledge existed for the channels. Since most processes and guidelines were created when traditional art studios were 90% of the business, little customer insight was captured for alternate channels.
- The consultant recommended that ArtSync undertake basic market research on customer and competitor, build personas for the channels, create customer-attribute segmentation, develop tailored content, and formulate a new lead scoring model.
After a target audience and competitive market analysis, the output was used to formulate marketing components identified earlier.
- Segmentation was based on relevant demographics, psychographics, behavioral characteristics, augmented with additional data capture upon launch.
- The content was developed that aligned with the interests, motives, and drivers for buyers in each channel, with adjustable update schedule driven by the initial response; preliminary customer journeys were used to organize content objects and page-level information architecture and guided by channel-specific workflows
- Training on platform and channel personas were provided to sales, marketing, and manufacturing
While the delay impacted short-term revenue, the new channel mix had mostly replaced leads and matched conversion rates from earlier success of the initial channel 90 days after relaunch. The sales cycle for the business was lengthy, but initial metrics strongly suggested revenue would soon match peak returns from traditional studio customers.
Choosing a Marketing Automation Platform
Businesses are often driven to adopt popular technology before defining specifically how the brand will leverage it to drive top performance goals.
Define Goals for Implementation
Marketing automation platforms can impact metrics all along the path from customer research to advocacy. As a result, brands should identify their top goals and likely functionalities employed to meet them: real-time customer analytics, more accurately qualified leads, improved content marketing efforts, etc.
Identify Metrics Connected to Goals
Once goals are prioritized, each goal, sub-goal, and each empowering functionality that supports the goals should be defined using specific metrics from the customer lifecycle. Later, when comparing platforms, the search leader should review tools that provide all key goal metrics throughout the process. Tying goals to live production metrics ensures the team is on track, makes post-implementation monitoring possible, and guarantees that stakeholders will be able to verify the investment.
Collaborate with Stakeholders
While the marketing team might initiate the selection process, collaboration with all impacted teams is essential for platform selection, and successful implementation. Only by surfacing pain points from sales will the platform accurately address sales-related processes. IT insights into company web assets and potential database and application integrations ensure compatibility issues and connectivity challenges do not disrupt implementation and timely rollout. Even manufacturing might be included at a high level, especially if increased sales or customization demands are expected to follow a marketing ramp-up.
Assess Brand Data and Platforms
The structural type of MA platform required depends greatly on the brand’s current data platforms and data volume. If a well-functioning CRM is in use finding a MA platform that integrates well is essential. If however, the brand has a smaller in-house database with limited functionality, a better choice may be a MA platform with built-in CRM functionality or a full sales-marketing-CRM-CMS cloud-suite. Any additional tools in use should be assessed to ensure critical analytics platforms, CDPs, or other marketing/sales toolsets are part of the decision process.
Business and Platform Alignment
While few platforms work only for B2C or B2B, or small business vs enterprise, many platforms are more aligned and optimized for specific business models. An expensive B2B product with a long cycle time might use long workflows and sequences spread over an extended timeline, or use extensive mobile functionality for an outside sales force. While a B2C e-commerce brand will gain from strong web analytics functions, extensive reporting that includes online behavior, and all key variables for online touchpoints. Many platforms identified During initial research, brands may find that their MA platform goals align with multiple functionality sets.
Assess Content and Web Assets
Most brands will use some form of content marketing and website functionality to provide the touchpoints for the customer journey. Depending on the marketing models, both content and other web assets should be prepared for expected use and volume at implementation.
- Does existing content cover all touchpoints in the defined journey? For all different segments? For any trends popularized on industry and vendor websites?
- Does the content volume and development plan meet expected demands for fresh content each month? Are internal resources enough, or do contract writers need to be identified?
- Is the blog optimized for search? Is it organized by customer segments and interests? Does the architecture support quick updates for custom landing pages?
- Are the brand website, product pages, checkout page, returning customer login, etc. all optimized to encourage prospects to easily find what they need and limit bounce?
Research Platform Options
There are few guardrails in the broad list of MA platforms: each product varies widely in features, and even standard functionality is implemented differently by each vendor. While research is key before adding any technology platform, with marketing automation, research (and goal-centric planning) are the guardrails protecting brands from a bad investment, poor results, and frustrating implementation.
- Teams responsible for procurement should start by reading background articles on the current state of marketing automation. Understand the trends, expectations for the market, and basic overview of industry offerings.
- Find a couple of recommended review aggregators like G2. Most good review aggregators will either sort or group by types of platforms–by business alignment (small businesses, start-ups, bloggers, enterprise), by structure (full cloud suite, standalone w/CRM built-in, automation for integrating with CRMs, CRM w/automation module), and cost factor (free, $100-500/month, $1000-5000/month). Editor reviews and current user reviews provide hands-on experience.
- Once interests are narrowed down to a top 4-5, brands should view vendor websites, review content, and detailed downloads (white papers, functionality comparisons, use cases, instructional videos). Most vendors provide case studies demonstrating ROI. After any further narrowing, take self-guided demos or contact a company representative for a walk-through demonstration.
- Identify products that meet current goals, and the key parts of the brand’s marketing roadmap.
Each product is designed to do some tasks better than others. Brands must determine which functionalities are most important for the goals and strategies, and select platforms that excel at these functionalities.
Define a Realistic Rollout
Each implementation timeline depends on the complexity of the business, the current infrastructure, and the resources applied. Estimates for initial adoption of a fully integrated platform can be up to 6 months, with real ROI with backing data taking even longer. In many cases, companies divide the implementation by functionality to create launches of specific functions earlier. Regardless, plan for significant time to complete all tasks.
- Installation and configuration
- Integration of all related data platforms
- Testing (unit testing of specific functions, full testing of end-to-end use)
- Training of all users (of any component, including reporting)
- Launch and monitor
With a user base comprising 75% of all businesses, marketing automation will continue to expand and apply to additional marketing practices and trends. Current functionality will increasingly be seen as an essential baseline. New functionality will likely use AI to combine advanced analytics and automated decisioning.
While current MA platforms automate many of the mundane tasks of the marketer, it also opens up the number of actions available during a campaign, ironically creating complexity as it seeks to simplify tasks. When MA’s abundant functionality is paired with AI-driven predictive analytics, all the advantages available to contemporary marketers could be aligned and focused to turn the potential of the MA platform into a new working model.
As a rules-based system with high data volume and ambiguity, marketing automation is a perfect match for machine learning algorithms to process, learn, and model. AI-driven lead scoring will recommend and execute actions based on exponential combinations of customer and product data, instead of scorecards derived from sales and marketer observations. The marketing mix and web assets will be defined at least partly on the automated predictive analysis of the most relevant touchpoints in customer journeys.
The past year was a testing ground for many companies, as they quickly ramped up to a predominantly digital and online marketing mix. Migrating tactics to an exclusively internet-based model revealed gaps and challenges. Brands that invested early in data science, and now nurture digital marketing maturity are positioned to test, experiment, and adopt technology-based solutions as they are developed. For many, the implementation of marketing automation is an impactful part of that investment in data-driven practices.
Akhtar, Omar. (2020). The 2020 State of Digital Marketing. Altimeter. https://www.prophet.com/download/the-2020-state-of-digital-marketing/
Recent analysis of the digital marketing world based on a survey of 476 senior digital marketers across North America, Europe, and China. Strong overview of current goals and challenges, trends, recap of 2020, spending, technology, current skills and processes, customer approaches, recommendations.
AutomateOnline. (2019, September 2). 20 Research-Backed Marketing Automation Stats You Should Know in 2020. https://automateonline.com.au/blog/20-research-backed-marketing-automation-stats-you-should-know
Collection of marketing automation statistics that are well-publicized in multiple online digital marketing journals.
G2. Best Marketing Automation Software. https://www.g2.com/categories/marketing-automation
Full-featured software review site, allowing buyers to filter by features, market segments, business types, review scores. A great place to start when selecting a new platform.
Galetto, Molly. (2017, November 2). Marketing Automation 101: The Complete Guide to Automating Your Marketing Actions to Do More in Less Time. NGDATA. https://www.ngdata.com/marketing-automation-101/.
Summarizes key benefits and structure of marketing automation platforms.
Gartner. (2020, November 11). Gartner Says Nearly 60% of Marketing Leaders Expect Moderate to Severe Cuts to Martech Budgets. Press release. https://www.gartner.com/en/newsroom/press-releases/2020-11-11-gartner-says-nearly-60–of-marketing-leaders-expect-m
Gartner assesses current martech utilization and techniques for more efficient use.
MediaBeacon. (2021, March 1). Digital Maturity for Marketing Processes. Esko. https://www.mediabeacon.com/en/blog/2018/digital-marketing-maturity-model-white-paper.
MediaBeacon, a digital and marketing asset management company, puts forth a white paper for a Marketing Digital Maturity Model of 5 levels, describing each level against six values at each level. The highest levels help illustrate the characteristics of thought leadership in digital marketing.
Miller, Jon. Mega-List of Features in Marketing Automation (That You Won’t Find in CRM). Marketo Blog. https://blog.marketo.com/2012/11/mega-list-of-features-in-marketing-automation-that-you-wont-find-in-crm.html
Created in 2012, but updated repeatedly since then without dates, however. Provides a significant list of functionalities that were rare at the time of first publication; however, many are still relevant, if now mainstream.
Moran, Matt. (2021, February 2). Marketing Automation Statistics. The Definitive List. https://funneloverload.com/marketing-automation-statistics/.
Collection of marketing automation statistics with annotation, covering top goals, top processes, MROI, barriers.
Orendorff, Aaron. (2016, December 19). The Three Levels of Marketing Automation & How to Decide. GetResponse. https://www.getresponse.com/blog/three-levels-marketing-automation.
Author makes a case for dividing marketing automation platforms by level of complexity.
be aware that collections of marketing statistics dated the current year can still contain 4-year-old stats pulled from elsewhere.
Redding, Shane. (2015). Can Marketing Automation be the Glue that Helps Align Sales and Marketing. Journal of Direct, Data, and Digital Marketing Practice (pp, 260-265).
Insightful discussion of marketing automation in B2B organizations through an interview with an experienced head of marketing, Andrea Collins, on large-scale partner-driven organization, practical applications, and lessons learned.
Rodriguez-Vila, Omar., Bharadwaj, S., Morgan, N. A., & Mitra, S. (2020). Is Your Marketing Organization Ready for What’s Next? Harvard Business Review. https://hbr.org/2020/11/is-your-marketing-organization-ready-for-whats-next
Reviews impact of recent technological change, and proposes a solution of creating new types of value propositions in addition to the traditional “exchange value” for customers. These include the “experience value” and “engagement value” for customers; the “strategic,” “operational” and “knowledge” values for the company. In the company example, “strategic” value is not expanding verticals or similar shifts, but monetizing an existing output. While customer experience and engagement have become a recent focus, in this model, both qualities are specific values equal to traditional exchange value, especially for near-commodities.
Wood, Claire. (2015). Marketing Automation: Lessons Learnt So Far. Journal of Direct, Data and Digital Marketing Practice. Vol. 16, N.4 (pp. 251-254).
Marketing Director for Deloitte, Claire Wood, discusses key fail points for implementation, including determining whether to implement, benefits for implementation, and what to expect.