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The marketing team at a multinational company needs to better understand their marketing effectiveness. The team is planning for the next fiscal year and must decide how to allocate budget to the various marketing channels. Spending must be cut by $1,000,000. The team needs to decide what they are not going to do next year. By using program analyzer, extracting the information, and populating an Excel sheet, the team is able to analyze the following data.
Based on the data from this year's marketing metrics, which conclusion can be made to help make decisions for next year?
The conclusion that can be made based on the data from this year's marketing metrics is that webinars provide the best ROI for acquiring new names because of the low cost, and tradeshows provide the least ROI because of the high cost. To help the company save money without sacrificing returns, they need to cut tradeshows by $1 million. This conclusion can be derived from analyzing the data in terms of cost per acquisition (CPA), return on investment (ROI), and budget allocation. Webinars have the lowest CPA ($10) and the highest ROI (900%) among all channels, which means they are the most efficient and effective way to acquire new names. Tradeshows have the highest CPA ($100) and the lowest ROI (100%) among all channels, which means they are the least efficient and effective way to acquire new names. Tradeshows also have the largest budget allocation ($1 million) among all channels, which means they are consuming a lot of resources without generating much value. Therefore, cutting tradeshows by $1 million will help the company reduce costs and increase returns.
A Sales team reports to Marketing that they receive false MQLs regularly. The Adobe Marketo Engage instance has three fields to track lead scores:
* "Total Score" is a sum of Behavior and Demographic Scores.
* A prospect gets graduated to MQL as soon as "Behavior Score" changes to 100 or greater and 'Demographic Score" must be at least 20.
* All "Demographic Score" smart campaigns are set up using "Person is Created" trigger with no filters.
The Marketo Engage Administrator audits the false MQLs and learns that most of them received a "Demographic Score" of +20 for being in a target "Job Title" and preferred "Country". Their "Demographic Scoring" was not completed. They received -10 for the "Industry" because these false MQLs are from Universities.
Which two sets of actions should the Architect take to stop sending the false MQLs to the Sales team? (Choose two.)
The two sets of actions that the Architect should take to stop sending the false MQLs to the Sales team are to use trigger ''Not Score is Changed'' on ''Demographic Field'' and to create a Boolean field and Smart-Campaign called ''Demographic MQL Score''. These actions will help the Architect to improve the lead scoring and qualification process, as well as to avoid sending leads that are not ready or qualified to the Sales team. Using trigger ''Not Score is Changed'' on ''Demographic Field'' will ensure that leads are scored only once based on their demographic attributes, instead of multiple times based on their behaviors. Creating a Boolean field and Smart-Campaign called ''Demographic MQL Score'' will enable the Architect to mark leads as Demographic MQLs based on their score and criteria, and to use this field as a filter and trigger for updating the MQL status.
An Architect notices that deliverability is slowly decreasing over time. After pulling a year of reports, the Administrator notices that the number of emails per month has increased from 3 to 10. The unsubscribe rates nearly double each quarter. Per the CMO, the amount of marketing activity must remain the same.
Which two actions can the Architectr take to make sure emails reach people in their database? (Choose two.)
Implementing communication limits and decreasing the number of email sends per month are two actions that can help improve deliverability by reducing email fatigue and spam complaints. Making marketing emails operational or decreasing behavior scores are not recommended as they can harm the sender reputation and engagement. Creating a ''marketable'' smart list is not relevant to the deliverability issue.
Refer to the case study.
UNICORN FINTECH COMPANY PROFILE
Unicorn Fintech is a mobile-only financial-servicesstartup created by a consortium of consumer banks to resell savings, checking, loan, transfer/remittance, and other services from a secure smartphone app. The company is venture-funded, and plans to reach profitability before a planned IPO in two years.
Business issues and requirements
Marketing is responsible for acquiring new customers 0 through online, television advertising, and email campaigns, and for cross-selling new services to customers through IM, email, and in-app campaigns. Evaluating the success of these campaigns has been a persistent problem: although the company can track revenue by product line, it can't attribute those revenues to campaigns: for example, did a new loan come from onboarding a new customer, or by cross-selling a savings-account customer? Marketing currently uses
crude, manual tools and guesswork to evaluate the quality and lifespan of new leads, and even the deliverability of emails in its external campaigns. As a result, the department can't allocate spending to the most productive campaigns, or decide how much different touchpoints in multi-stage campaigns contribute to revenue. Operational processes to connect lead data to CRM and other databases are entirely manual.
Staffing and leadership
Unicorn has fewer than 200 employees, and roles aren't always defined in traditional ways. Since customer acquisition and cross-selling are primarily through electronic channels, Marketing and IT roles especially often overlap. The traditional Sales role falls entirely to Marketing, and IT is responsible for the Salesforce CRM system, Google Analytics, and a handful of third-party integrations. The CMO and CIO work closely together on most initiatives, and budgets are typically project-driven rather than fixed annually. Individual contributors to Marketing campaigns include the Marketing Operations Manager, responsible for lead scoring and analytics. Key IT contacts include the CRM Administrator and Web Developer. Incidental contributors are the Corporate Attorney, who signs off on opt-in/out and DMARC policies.
Revenue sources
Unicorn earns commissions on financial services delivered by the banking consortium through its apps, including fixed finders' fees for what the company calls "skips"-customers who initially engage with Unicorn, but then "skip" to receive services directly from a consortium bank. Unicorn needs to attribute revenue from these customers to its own campaigns; currently, it's impossible to attribute ROI to individual campaigns, or provide documentation to claim commissions on "skips."
Current and aspirational marketing technology
Current Marketing technology consists of Marketable,an open-source lead management solution supported by a set of spreadsheets and scripts developed in-house. Marketable offers lead tracking and source attribution, but not multi-touch source attribution. Unicorn Fintech Marketing has difficulty linking the different stages of customer campaign journeys, and relies on scripts to translate Marketable's "sales alerts" into next steps it could use in multi-touch campaigns. IT has worked out scripts to input Marketable qualified leads into Salesforce, but the system is brittle and often requires manual intervention.
Current campaign management processes
A typical email campaign:
* Addresses a purchased (for customer acquisition) or0 in-house (for cross-sell) list. Purchased lists range from 300,000 to 1.5 million addresses
* Is sent from multiple data centers in the US and Canada
* Includes an "unsubscribe" opt-out below the message
* Is static; there are no formula fields
* Uses no deliverability authentication, nor integration 0 with any email management platform.
All campaigns to date direct respondents to a single 0 landing page with the company's "all markets" message. More sophisticated targeting is a high priority.
Current lead management and attribution
Unicorn's lead-management process follows
Marketable's "out of the box" defaults: lead evaluation levels 1 through 3, lifecycle stages "unqualified" and "qualified." The qualification processes are manual, and highly subjective: Marketing staff classify leads according to prospect email responses, including free-form comments. "Sales" followup is by email forms prompting higher levels of engagement. The company intends to phase out Marketable and replace spreadsheets and scripts with native features of whatever solution set it adopts.
Attribution processes are binary: response to a campaign email or web visit is rated a success if it results in a sale: there is no success rating assigned to TV ads that result in web visits, for example. Cost are not allocated to individual campaigns.
The Marketing department plans to expand outreach to social media (Facebook, Twitter, Instagram, in-house and third-party financial blogs), and wants to make sure it can assess the ROI of these channels, and the overall social media program.
Current governance processes
Currently, the Marketing department assigns content development and campaign management duties to team members on a campaign-by-campaign basis. All team members (and IT) have access to all assets and tools, which sometimes leads to duplication and conflicts. The CMO realizes that a more specialization will be necessary to support the social media campaigns, but hasn't decided on the optimal organizational model.
Input of qualified leads from Marketable into
Salesforce is by manual cut-and-paste, assisted by scripts; inconsistency of input practices across Marketing team members is a known problem; individual members have their own "go-to" fields: where one member might check "TV ad" as Lead Source, another would put that in the comments field.
CMO
The CMO's most important concerns are:
* The current solution has too many manual steps to scale with anticipated growth
* Without more sophisticated attribution, the company will overinvest in less productive campaigns, and underinvest in better ones
* In general, analytics integrations are manual, slow, and unreliable
* The current system completely misses "skips"-customers switching from the Unicorn app to consortium banks-an important source of revenue
* Documenting the value of Unicorn's Marketing processes is essential to the success of the planned IPO, and millions of dollars in stock valuation hangs in the balance.
CIO
The CIO is concerned primarily with:
* The amount of time his team spends patching up Marketing campaigns and CRM data transfers, at the expense of other, critical initiatives
* Quality and reliability of the Analytics information his team provides to Marketing
MARKETING STAFF
Marketing Operations staff concerns:
* Campaigns require so much work that they can't run as many of them as they need to
* Multi-touch cross-selling campaigns (for example, savings accounts to loans) with excellent margins, but no way to know which campaign touches perform best
* Getting swamped with manual record-keeping; for example, spreadsheet mistakes take hours to find and
fix
* Poor integration with third-party tools for preparing, sending, and evaluating campaign materials, for
Example.
o Webhook not firing,
o Reaching API limit
o Synchronization errors with third-party tools and Salesforce
* Inadequate number of lead stages and qualification levels, making it difficult to evaluate lead value, especially in multi-touch campaigns
Despite the absence of an external Sales team,
Marketing Operations would like to improve the granularity of their lead tracking, including both lifecycle stages and quality levels, with "no score" and negative levels.
Unicorn Fintech needs to revamp its scoring model.
Who should be involved in making decisions on what behaviors should be scored?
Marketing Operations Manager, CRM Administrator, CMO, and a sales team representative should be involved in making decisions on what behaviors should be scored. The Marketing Operations Manager is responsible for lead scoring and analytics, the CRM Administrator is responsible for the Salesforce CRM system, the CMO is responsible for the overall marketing strategy and budget, and a sales team representative can provide feedback on the quality and readiness of the leads. The CIO and the Web Developer are not directly involved in the scoring model, as they are more focused on the technical aspects of the marketing technology and integrations.
Refer to the lifecycle model above.
A company wants improve the efficiency of its sales follow-up and enhance its velocity reporting across the funnel. The company currently uses the out-of-box Adobe Marketo Engage success with detours modeler. The stages are defined as:
1. Anonymous: Leads whose web activity is tracked, but whose identity is not known yet
2. Known: Leads for whom we have an email address or other information that allows us to market to them
3. Engaged: Leads that have engaged us by filling out a form, clicking a link in an email, or visiting our website at least 10 times within a week
4. Lead: Leads with scores greater than 25
5. Sales Person: Leads with scores greater than 30
6. Opportunity: Leads who also have an opportunity attached to them. The Max Age is set to 7 days before it moves to "Lost".
7. Won: Leads who are attached to opportunities that we have closed and Won
8. Recycling: People with scores below 25 that need to be nurtured
9. Disqualified: People who are not a fit for our products and services and we no longer want to market to them
0. Lost: People who are attached to opportunities that we have lost
Once leads reach the "Sales Person" stage, 50% of them do not get followed up by Sales until 7 days later. The Sales leader wants a salesperson to follow up with leads within 4 days.
Which two modifications should the Adobe Marketo Engage Consultant make to the lifecycle model to achieve these goals? (Choose two.)
The two modifications that the Adobe Marketo Engage Consultant should make to the lifecycle model to achieve these goals are to add an additional stage between ''Sales Person'' and ''Opportunity'' and to modify the Sales Person stage from Type: Gate to Type: SLA. These modifications will help the company to improve the efficiency of its sales follow-up and enhance its velocity reporting across the funnel, as well as to ensure that a salesperson follows up with leads within 4 days. Adding an additional stage between ''Sales Person'' and ''Opportunity'' will enable the Consultant to create a separate stage for leads that are being worked by Sales but have not yet become opportunities, as well as to measure the conversion rate and velocity of this stage. Setting type to SLA and setting Max Age to 3 days for this stage will enable the Consultant to define a service level agreement (SLA) between Marketing and Sales, as well as to monitor and measure the compliance and performance of Sales. Modifying the Sales Person stage from Type: Gate to Type: SLA will enable the Consultant to specify the maximum time that a lead can stay in the Sales Person stage before it is moved to another stage or marked as non-compliant. Setting Max Age to 4 days for this stage will enable the Consultant to align with the Sales leader's goal of following up with leads within 4 days.
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