Madison Logic’s platform for account-based marketing leverages first-party, third-party, and proprietary sources for intent, technographic, firmographic, and audience data to improve account and contact targeting and content relevancy. In addition, the platform provides personalized engagement through syndicated marketing content and programmatic display advertising campaigns. Madison Logic’s account-based insights and hyper-targeting solution, Journey Acceleration™, can be integrated with a marketer’s CRM and marketing automation platform to drive stronger engagement with companies and to become more agile for moving companies through the marketing funnel.
Madison Logic commissioned Forrester Consulting to conduct a Total Economic Impact™ (TEI) study and examine the potential return on investment (ROI) enterprises may realize by deploying the Madison Logic solution. The purpose of this study is to provide readers with a framework to evaluate the potential financial impact of the Madison Logic Platform on their organizations.
To better understand the benefits, costs, and risks associated with this investment, Forrester interviewed four customers with experience using the Madison Logic solution integrated with platforms like Salesforce and Marketo. Based on four Madison Logic customer interviews, Forrester created a composite organization to illustrate the benefits and costs associated with an investment in the Madison Logic ABM platform.
Profit growth from improved volume in marketing-qualified accounts:
Profit growth from improved account conversion after deploying Madison Logic:
Madison Logic software licensing and marketing costs:
Quantified benefits.The following risk-adjusted present value (PV) quantified benefits are representative of those experienced by the companies interviewed:
Interviewed customers previously had to sift through numerous poor accounts to eventually find a few warm prospects and then qualify them. In campaigns using Madison Logic, the percentage of marketing accounts that became qualified per campaign reached 9% or triple the previous qualification rate. Intent and engagement data delivered by Madison Logic’s Journey Acceleration offering enabled sales teams to identify accounts that were at a mature stage in the marketing funnel. Among the total volume of accounts that were qualified from campaigns using Madison Logic as a touchpoint, 72% were attributable to the platform.
In campaigns that did not use Madison Logic, the interviewees reported that their conversion rate for closed accounts hovered around an average of 2%. When leveraging intelligence from Madison Logic’s Data Cloud to create more relevant content and improved targeting, the organizations were able to improve sales conversion rates from 2% in Year 1 to 4% in Year 3.
Instead of providing discrete alerts or signals of buyer behavior, Madison Logic’s platform provided sales teams with an easy-to-interpret engagement score showing the surge in interest on specific topics. These data points were readily accessible to sales and marketing teams through Madison Logic’s integrations with Salesforce and Marketo. As a result, sales professionals spent less time gathering information to qualify an account that would take roughly 6 hours without Madison Logic; for campaigns using Madison Logic, it took on average 2 hours per account.
Unquantified benefits. The interviewed organizations experienced the following additional benefits, which are not quantified for this study:
For interviewed businesses that were marketing transactional products, which generally have a short sales timeline, the shortened time spent qualifying accounts improved deal velocity. However, negotiations for larger deals tied to subscription and long-term services could still carry on for months as they did before Madison Logic. The level of variability for types of deals being closed is why deal velocity wasn’t factored into the financial model. Organizations that would like to calculate their deal velocity can multiply their number of opportunities, deal value, and sales conversion rate against each other, then divide it by the length of sales cycle.
Time savings realized by the organizations varied based on the number of campaigns run. An organization running six campaigns through Madison Logic was able to carve out over 2 hours of weekly labor savings compared to an organization that ran two campaigns, which saved 1 hour of work per week.
Costs. The interviewed organizations experienced the following risk- adjusted PV costs:
Licenses for Madison Logic are paid on a monthly basis. Meanwhile, costs for demand generation content and display advertising campaigns through the platform scale based primarily on list size.
On average, organizations had two FTE employees primarily responsible for creating content or management of the campaigns through the platform. An additional FTE employee dedicated a portion of their time to managing the sharing of engagement data between the marketing and sales teams. Interviewed organizations reported that implementation and maintenance of the Madison Logic platform was user-friendly and did not incur additional costs for employee upkeep.
Forrester’s interviews with four existing customers and subsequent financial analysis found that an organization based on these interviewed organizations experiences benefits of $7,274,481 over three years versus costs of $1,198,893, adding up to a net present value (NPV) of $6,075,588 and an ROI of 507%.
From the information provided in the interviews, Forrester has constructed a Total Economic ImpactTM (TEI) framework for those organizations considering implementing Madison Logic’s platform.
The objective of the framework is to identify the cost, benefit, flexibility, and risk factors that affect the investment decision. Forrester took a multistep approach to evaluate the impact that Madison Logic can have on an organization:
Interviewed Madison Logic stakeholders and Forrester analysts to gather data relative to Madison Logic.
Interviewed four organizations using Madison Logic to obtain data with respect to costs, benefits, and risks.
Designed a composite organization based on characteristics of the interviewed organizations.
Constructed a financial model representative of the interviews using the TEI methodology and risk-adjusted the financial model based on issues and concerns of the interviewed organizations.
Employed four fundamental elements of TEI in modeling Madison Logic’s impact: benefits, costs, flexibility, and risks. Given the increasing sophistication that enterprises have regarding ROI analyses related to IT investments, Forrester’s TEI methodology serves to provide a complete picture of the total economic impact of purchase decisions. Please see Appendix A for additional information on the TEI methodology.
Readers should be aware of the following:
This study is commissioned by Madison Logic and delivered by Forrester Consulting. It is not meant to be used as a competitive analysis.
Forrester makes no assumptions as to the potential ROI that other organizations will receive. Forrester strongly advises that readers use their own estimates within the framework provided in the report to determine the appropriateness of an investment in Madison Logic.
Madison Logic reviewed and provided feedback to Forrester, but Forrester maintains editorial control over the study and its findings and does not accept changes to the study that contradict Forrester’s findings or obscure the meaning of the study.
Madison Logic provided the customer names for the interviews but did not participate in the interviews.
|INDUSTRY||REGION||INTERVIEWEE||NUMBER OF CAMPAIGNS USING MADISON LOGIC PER YEAR|
|Security||Headquartered in the United States||Manager of marketing operations and business development||4|
|B2B||Headquartered in the United States||Head of marketing and demand generation||2|
|Utilities||Headquartered in the United States, customers globally||Media strategist||4|
|B2B||Headquartered in the United Kingdom, customers globally||Digital marketing and online media manager||6|
Interviewees shared several challenges that they faced when running marketing campaigns, including:
A couple of the marketing managers noted that their marketing budgets often leave them constrained from creating robust campaigns that include display advertising, webinars, and video content. Often, marketers can only afford to create a handful of marketing materials and target a limited number of accounts. Given that marketing campaigns are often associated with sales goals, efficient marketing is an ongoing challenge for marketing teams.
Marketing managers expressed frustration with their marketing efforts yielding a disappointingly low number of qualified accounts or poor accounts altogether. One customer reported that a campaign targeting 2,000 accounts on another ABM platform produced just 2% to 5% qualified accounts. Several factors accounted for this, including the types of partners used by the platform for content syndication and a lack of insight into relevant topics for targeting accuracy.
Several of the interviewees noted that sales teams would often spend time targeting accounts that they later found out were cold. Frequently, blast emails and mass marketing campaigns generated a large list of accounts; however, the accounts tended to be low-quality and not worth pursuing.
Marketing managers were confident that they produced relevant content for targeted accounts yet didn’t have insight into which topic areas resonated with an account’s target audience. This lack of engagement insight stifled the process for helping targeted contacts progress in their buying journeys.
The interviews revealed that key results from the Madison Logic investment include:
Organizations used intelligence from Madison Logic’s Data Cloud to improve efficiency in their marketing campaigns. Content creators on marketing teams crafted demand generation content and display creative that was more relevant to target accounts, resulting in higher engagement. “For me, the reliability of the performance of the content is a top benefit. I don’t have a large budget for my campaigns, so I need to make sure that the money I spend is going to generate the right kind of accounts,” said the head of marketing and demand generation at a B2B company. “Sales is going to believe in them and follow up with them and then, it’s going to turn pipeline into closed business.”
Madison Logic produced warmer accounts than previous solutions for customers because they could identify why accounts were engaging with their content. Further measurement of engagement and intent surrounding marketing content helped sales teams to qualify their accounts. “Being able to identify the companies that are searching on our website and being able to identify which topics they are searching on is very helpful to our sales team,” said a media strategist at a utilities company. “Especially when they’re looking to match names to solutions they may have been researching.”
According to interviewees, Madison Logic’s integrations with CRM and marketing automation platforms prepared their sales teams with the necessary information to best communicate with targets. “Running a comprehensive demand program with digital advertising and then seeing the increase in accounts engaging on our site is a key feature of Madison Logic. We’re able to have a more personalized message and intelligent conversations with accounts, using those data signals that Madison Logic provides,” said a digital marketing manager at a B2B software company.
Marketers at the organizations were able to keep sales teams more up to speed on where accounts were in the marketing funnel. “Now we’re including salespeople as we’re reaching out to their accounts and letting them know about these campaigns we have going on. We’re letting them know the messages going out to those accounts, so they are better equipped when they’re following up,” said one interviewee.
Based on the interviews, Forrester constructed a TEI framework, a composite company, and an associated ROI analysis that illustrates the areas financially affected. The composite organization is representative of the four companies that Forrester interviewed and is used to present the aggregate financial analysis in the next section. The composite organization that Forrester synthesized from the customer interviews has the following characteristics:
The composite organization is a US-based B2B software company with annual revenues totaling $100 million worldwide and annual marketing spend of $10 million, with $3 million of that spend dedicated to the US. Since its creation in 2010, the organization has grown to include 1,000 employees, 35 of whom are on the marketing team. The company has used display advertising and some demand generation for account-based marketing thus far and is looking to add another comprehensive demand generation platform to its funnel to improve targeting and marketing-qualified account volume.
The B2B organization adopts the Madison Logic platform and dedicates two FTEs to producing content and managing the platform. In Year 1, the composite pilots demand generation content and display advertising through Madison Logic with two marketing campaigns, targeting 2,000 US-based accounts in each campaign. By Year 2, Madison Logic is used in four marketing campaigns annually.
|Ref.||Benefit||Year 1||Year 2||Year 3||Total||Present Value|
|Atr||Profit growth from improved volume in marketing-qualified accounts||$877,500||$1,755,000||$1,755,000||$4,387,500||$3,566,698|
|Btr||Profit growth from improved account conversion after deploying Madison Logic||$0||$1,215,000||$2,430,000||$3,645,000||$2,829,827|
|Ctr||Cost savings from reduction in time spent qualifying accounts||$216,000||$432,000||$432,000||$1,080,000||$877,956|
|Total benefits (risk-adjusted)||$1,093,500||$3,402,000||$4,617,000||$9,112,500||$7,274,481|
The table above shows the total of all benefits across the areas listed below, as well as present values (PVs) discounted at 10%. Over three years, the composite organization expects risk-adjusted total benefits to be a PV of nearly $7.3 million.
Madison Logic’s influence on the pipeline of marketing-qualified accounts starts with its deliverance of warm accounts (i.e., a contact who has engaged with a piece of marketing content) and engaged B2B influencers within those accounts through aligned digital advertising. Each of the interviewed organizations reported that the share of warm accounts returned from those targeted in campaigns rose dramatically when using Madison Logic, with a couple reporting a jump from 10% to a 99% return rate.
The high return rate is primarily driven by the campaigns using Madison Logic’s Journey Acceleration and data intelligence to be more hyper-targeted to accounts. Customers can provide their own list of target accounts, via a file or through integrations with their CRM and marketing automation platforms, or they can use Madison Logic to refine or compile a list of accounts based on a selection of intent topics, technographic, firmographic, and audience filters to identify where engagement is trending.
While warm accounts are helpful, Madison Logic proves its value by providing context on accounts to qualify them. Previously, marketers could not identify if an individual downloading a whitepaper or viewing a webinar was from a high-quality account and actively interested in the marketed product solution. Madison Logic’s Data Cloud provides insights around those downloads — specifically, which intent topics are driving account interest, the number of times an account contact has visited a site, and the number of individuals engaging from the same account.
Alongside demand generation content, Madison Logic also offers the ability to run display advertising campaigns using its Data Cloud. Although the marketing managers noted that they still used additional display ad platforms as touchpoints in their campaigns, they did speak to its usefulness in creating a comprehensive marketing program. “The fact that we can couple programmatic with the demand generation portion makes any leads we have that much stronger. In a sense that we may not close on the lead but can collect intelligence on the account behind the scenes,” said the digital marketing and online media manager at a B2B company.
Because of Madison Logic’s account indicators for engagement, the marketers were better informed to create more relevant content for their targets, as well as to become more accurate when qualifying accounts.
For the composite analysis, Forrester assumed the following, based on information collected from the interview responses:
The B2B company targets 2,000 accounts per campaign.
Before Madison Logic, sales professionals at the organization were able to qualify 2.5% of its accounts, or 50 accounts total. After deploying the platform, campaign targeting improves, and sales professionals are able to qualify 9% of accounts or triple the previous the rate. Of the 180 new marketing qualified accounts, 130 are attributable to Madison Logic.
Madison Logic delivers $1.3 million in revenue growth from additional account volume in Year 1 while being test piloted in two marketing campaigns. In both Years 2 and 3, the platform is incorporated into four marketing campaigns and delivers $2.6 million in additional revenue.
The interviews included organizations based in B2B, security, and utilities verticals with profit margins ranging from 15% to 60%. To be conservative, the composite organization has an operating profit margin of 25%.
The following are the potential risks that may affect this benefit:
If an organization plans to implement Madison Logic in a campaign that targets a larger number of accounts, the growth in percentage of qualified accounts may skew smaller. A couple of the interviewed organizations reported that Madison Logic helped most when marketing to a smaller specific set of accounts, allowing for more concise messaging and precise targeting.
Interviewed organizations noted that their Madison Logic-enabled marketing campaigns reserved roughly three-quarters of their budget for demand generation content to one-quarter for display advertising. As a result, the model is more reflective of campaign performance for demand generation content-heavy campaigns.
The operating profit margin will vary company to company based on annual marketing spend. Factors that impact spending include length and aggressiveness of the campaign, reliance on demand generation vs. display advertising, and the company’s business model.
To account for these risks, Forrester adjusted this benefit downward by 10%, yielding a three-year risk-adjusted total PV of $3,566,698.
Impact risk is the risk that the business or technology needs of the organization may not be met by the investment, resulting in lower overall total benefits. The greater the uncertainty, the wider the potential range of outcomes for benefit estimates.
|Ref.||Metric||Calc.||Year 1||Year 2||Year 3|
|A1||Number of targeted accounts per campaign||2,000||2,000||2,000|
|A2||% marketing-qualified accounts prior to using Madison Logic||Customer interviews||2.5%||2.5%||2.5%|
|A3||Number of marketing-qualified accounts prior to deploying Madison Logic||A1*A2||50||50||50|
|A4||% marketing-qualified accounts after deploying Madison Logic||Customer interviews||9%||9%||9%|
|A5||Number of marketing-qualified accounts after deploying to Madison Logic||A1*A4||180||180||180|
|A6||Number of marketing-qualified accounts attributable to Madison Logic||A5-A3||130||130||130|
|A7||Baseline accounts converted to closed||Assumption||2%||2%||2%|
|A8||Average deal size||$750,000||$750,000||$750,000|
|A9||Campaigns using Madison Logic per year||2||4||4|
|A10||Growth in sales from improved volume in marketing-qualified accounts||A6*A7*A8*A9||$3,900,000||$7,800,000||$7,800,000|
|A11||Operating profit margin||25%||25%||25%|
|At||Profit growth from improved volume in marketing-qualified accounts||A10*A11||$975,000||$1,950,000||$1,950,000|
|Atr||Profit growth from improved volume in Atr marketing-qualified accounts (risk-adjusted)||$877,500||$1,755,000||$1,755,000|
Sales teams that receive Madison Logic accounts have better, more informed conversations with prospective customers. As marketing teams use intent, technographic, and engagement data to create more relevant content for accounts, they can also use data pulled from content engagement to inform their sales teams when approaching them.
“My budget was cut last year,” said the manager of marketing operations at a security company. “Madison Logic became the No. 1 program I run on the demand side, just because I know the return that I get, and the quality that I get. And that’s something that I can work with for a full year.”
A couple of the interviewed organizations spoke to their marketing and sales teams experiencing improved alignment since adopting Madison Logic. There is regular communication between marketing and sales teams about the most targeted pieces of content to send prospective accounts depending on where content engagement is trending (e.g., growth in report views, downloads).
Through partnerships with Salesforce and Marketo, marketing teams can automatically upload engagement dashboards and data including downloads and views from marketing campaigns to account pages in Salesforce or to custom activities in Marketo. Previously, engagement data would take roughly 1 to 2 hours to clean and prepare in a spreadsheet for uploading. During that process, data would occasionally go missing or be uploaded to the wrong account. Today, salespeople at the interviewed organizations are aware of where accounts are in the sales funnel and what is driving interest.
Even with a greater number of marketing-qualified accounts, sales teams still have limited time to close accounts. By using insights from Madison Logic’s Data Cloud, especially when its readily available in Salesforce, sales teams are more agile and capable of carving out time to close additional accounts when using Madison Logic.
For the composite analysis, Forrester assumed that:
The B2B company closed 2% of its 180 marketing-qualified accounts annually prior to using Madison Logic. At this rate, two marketing campaigns generated $1.8 million and four marketing campaigns produced $3.6 million.
After deploying Madison Logic in campaigns, the conversion rate hovers around 2% in Year 1. This is primarily a result of the organization receiving new accounts in Year 1, but finally closing on them in Year 2. Due to a higher number of qualified accounts, the conversion rate grows to 3% in Year 2. Conversions rise again in Year 3 to 4%, helped by the sales team’s increased trust in the quality of accounts and intent data.
Improvement on sales account conversion will vary:
An organization may not be able to consistently close a high rate of accounts annually because of prolonged sales cycles. Thus, some conversions may contribute to the following year’s profit.
Not all organizations have integrated Madison Logic with Marketo and will not have the same level of communication and collaboration between marketing and sales.
To account for these risks, Forrester adjusted this benefit downward by 10%, yielding a three-year risk-adjusted total PV of $2,829,827.
|Ref.||Metric||Calc.||Year 1||Year 2||Year 3|
|B1||Number of marketing-qualified accounts after deploying Madison Logic||A5||180||180||180|
|B2||Accounts converted to closed before deploying Madison Logic||2%||2%||2%|
|B3||Average deal size||A8||$750,000||$750,000||$750,000|
|B4||Campaigns using Madison Logic per year||2||4||4|
|B5||Sales from marketing-qualified accounts||B1*B2*B3*B4||$5,400,000||$10,800,000%||$10,800,000|
|B6||% of accounts converted to close after Madison Logic||2%||3%||4%|
|B7||Sales from increased conversion of accounts after deploying Madison Logic||B1*B6*B3*B4||$5,400,000||$16,200,000||$21,600,000|
|B8||Increase in sales from improved account conversion after deploying Madison Logic||B7-B5||$0||$5,400,000||$10,800,000|
|B9||Operating profit margin||25%||25%||25%|
|Bt||Profit growth from improved account conversion after deploying Madison Logic||$0||$1,350,000||$2,700,000|
|Btr||Profit growth from improved account conversion after deploying Madison Logic (risk-adjusted)||$0||$1,215,000||$2,430,000|
The process for qualifying accounts can be drawn out for marketers, compounded by the need to determine key topics for the critical opening communication with prospects. Madison Logic accelerates the qualification timeline through its alerts on increasing engagement around display ads, syndicated content, website activity, intent, and other signals. Through these identifiers, businesses can align messaging with the right accounts.
“At an early stage, we’re just trying to add new context sources for accounts, making sure that we’re able to speak to all of the buyers that are in the buying committee, driving movements to our site and just trying to get them engaged,” said the digital marketing and media manager at a B2B company. Marketers were able to use Madison Logic throughout the marketing campaign, syndicating content via the platform to produce accounts and then targeting those accounts with display advertising. Engagement with these pieces of content throughout a comprehensive marketing campaign builds a profile of an account and helps sales teams to confidently qualify accounts.
According to one interviewee at a small-sized organization, at a high level, time spent qualifying an account was reduced from three months to one month. This timeline varied for large-sized businesses, but they were consistent in noting a significant time decrease for qualifying accounts. As a result, sales teams were able to close on more accounts.
For the composite analysis, Forrester assumed that:
The sales team spends roughly 6 hours on qualification per account on campaigns that do not involve Madison Logic. For campaigns using Madison Logic, time spent qualifying each account falls to 2 hours. For each campaign, the total time saved on qualifying accounts is 8,000 hours.
The fully burdened hourly salary of a sales team member is $30. Fifty percent of the time saved qualifying accounts is put toward value-add tasks, as not all saved time is necessarily devoted to the business. (It could be rededicated to time spent on social media or conversing with coworkers or a reduction of work hours.)
The B2B company saves $240,000 from reduced time spent qualifying accounts in Year 1 when running two campaigns. In Years 2 and 3, the business saves $480,000 when running four campaigns.
The following are the potential risks that may affect this benefit category:
Time spent qualifying accounts can vary based on the account-based marketing platform being used for marketing campaigns. Some platforms may provide indicators that expedite the qualification process at a faster rate than 6 hours, leading to a smaller savings in time.
To account for these risks, Forrester adjusted this benefit downward by 10%, yielding a three-year risk-adjusted total PV of $877,956.
|Ref.||Metric||Calc.||Year 1||Year 2||Year 3|
|C1||Number of targeted accounts per campaign||2,000||2,000||2,000|
|C2||Hours spent qualifying per marketing account before deploying Madison Logic||Customer interviews||6||6||6|
|C3||Hours spent qualifying per marketing account after deploying Madison Logic||Customer interviews||2||2||2|
|C4||Hours saved qualifying per account after deploying Madison Logic||C2-C3||4||4||4|
|C5||Total hours saved per account per campaign||C1*C4||8,000||8,000||8,000|
|C6||Campaigns using Madison Logic per year||2||2||2|
|C7||Cost per hour of sales team FTE effort||$30||$30||$30|
|C8||Percent recaptured for productivity||50%||50%||50%|
|Ct||Cost savings from reduction in time spent qualifying accounts||C5*C6*C7*C8||$240,000||$240,000||$240,000|
|Ctr||Cost savings from reduction in time spent qualifying accounts (risk-adjusted)||$216,000||$432,000||$432,000|
The value of improved deal velocity from a reduction in time spent qualifying accounts has not been factored into benefit analysis:
Deal velocity varied for the organizations based on the scale of the transaction. For interviewed businesses that were marketing transactional products, which generally have a short sales cycle, the shortened time spent qualifying accounts improved deal velocity. However, negotiations for larger deals tied to subscription and long-term services could still carry on for months as they did before Madison Logic. Due to these varying factors, improvement in deal velocity varied too greatly to factor into the benefits.
Organizations that had integrated Madison Logic with Marketo noted that they no longer had to spend 1 to 2 hours formatting and cleaning data on accounts in spreadsheets for ingestion to Salesforce. While the cost savings from reduction in time spent on the task was small, it was a notable stress relief for the interviewees.
The value of flexibility is clearly unique to each customer, and the measure of its value varies from organization to organization. There are multiple scenarios in which a customer might choose to implement Madison Logic and later realize additional uses and business opportunities, including:
A couple of the interviewed businesses had not taken full advantage of all of Madison Logic’s integration capabilities with Marketo to improve targeting for automated marketing campaigns through the platform because of a lack of team bandwidth to see through planning.
In addition, the digital marketers who had not integrated were unable to take advantage of identifying engagement trends, particularly in relation to where an account was in the marketing funnel. For a couple of the interviewed organizations that had conducted the integration, this information improved communication between marketing and sales. “Because of the data matching so perfectly and the targeting of the campaign being spot on, I don’t have to pound on sales like, ‘Hey, go through these accounts and prioritize them, and see which ones are good or not.’ They know that they’re able to follow up on a hot lead,” said an interviewee.
The organizations that had yet to take advantage of the integration planned to. “We’ve had to do a lot of educating because there was some resistance from the sales team at the beginning to an automated process,” said one interviewee. “But as we are starting to have more wins, they are more open to integrating on these types of campaigns.”
After a business runs a marketing campaign through Madison Logic, it can carry on the insights it learned from the platform and apply toward future campaigns — specifically, which pieces of content and topic areas resonated most with targeted accounts, alongside which stages of the sales cycle were most effective for deploying demand generation content or display ads. This information could better inform targeting for future campaigns through Madison Logic and topics to cover for content.
One interviewee mentioned that Madison Logic helped the organization reconsider account targets to prioritize. “We were expecting to get accounts for the top 200 accounts that we had shared. But what we found were accounts further down our lists that we had to shift our focus to,” said the interviewee. The accounts were based in industries the organization had not currently targeted and helped guide targeting in the next campaign to accelerate its pipeline.
Madison Logic offers a content services team to help create content for businesses that need assistance in output. This service was primarily used by organizations interviewed that didn’t have the bandwidth to produce more marketing content. “We use their content services team to help out with digital advertising part. They help us create top-of-funnel, mid-funnel, and bottom-funnel campaigns for digital ads,” said an interviewee. “I send them a couple of assets and what our messaging would be for an asset for top of funnel versus mid-funnel versus bottom funnel. Then they handle all that for me, as well as the optimization for targeting and pushing through Marketo.” Marketing teams that use these services could potentially avoid needing an additional FTE to at least one-quarter of their time to producing marketing content.
Most of the marketing managers had primarily used Madison Logic to help hyper-target accounts in small scale campaigns. The interviewees indicated that they intend to use the platform in more campaigns now that it had gained sales’ trust. However, marketing budgets determined additional usage of the platform.
Flexibility, as defined by TEI, represents an investment in additional capacity or capability that could be turned into business benefit for a future additional investment. This provides an organization with the "right" or the ability to engage in future initiatives but not the obligation to do so.
|Ref.||Cost||Initial||Year 1||Year 2||Year 3||Total||Present Value|
|Htr||Madison Logic software licensing and marketing costs||$0||$198,000||$363,000||$363,000||$924,000||$752,727|
|Itr||Ongoing Madison Logic FTE support costs||$0||$179,410||$179,410||$179,410||$538,230||$446,166|
|Total costs (risk-adjusted)||$0||$377,410||$542,410||$542,410||$1,462,230||$1,198,893|
The table above shows the total of all costs across the areas listed below, as well as present values (PVs) discounted at 10%. Over three years, the composite organization expects risk-adjusted total costs to be a PV of nearly $1.2 million.
Licenses for Madison Logic are paid on a monthly basis. Meanwhile, costs for demand generation content and display advertising are based primarily on list size.
For the composite analysis, Forrester assumes:
The composite B2B organization pays a $2,500 monthly fee for the Madison Logic platform, averaging $30,000 annually.
Demand generation content syndicated through Madison Logic’s platform accounts for 80% of the marketing budget per campaign annually, while display advertising represents 20%.
The B2B organization maintains a consistent spend per campaign throughout the three-year period while increasing the number of campaigns from two to four in Years 2 and 3.
As for risks, the marketing budget will vary depending on the scale of the marketing campaign and spend being allocated more toward demand generation content or display advertising.
To account for these risks, Forrester adjusted this cost upward by 10%, yielding a three-year risk-adjusted total PV of $752,727.
Implementation risk is the risk that a proposed investment may deviate from the original or expected requirements, resulting in higher costs than anticipated. The greater the uncertainty, the wider the potential range of outcomes for cost estimates.
|Ref.||Metric||Calc.||Initial||Year 1||Year 2||Year 3|
|H1||Madison Logic software licensing and maintenance fees per year||$30,000||$30,000||$30,000|
|H2||Marketing spend per campaign dedicated to demand generation through Madison Logic||$60,000||$60,000||$60,000|
|H3||Marketing spend per campaign dedicated to display advertising through Madison Logic||$15,000||$15,000||$15,000|
|H4||Total marketing spend per campaign dedicated to Madison Logic||H2+H3||$75,000||$75,000||$75,000|
|H5||Number of marketing campaigns per year||2||4||4|
|Ht||Madison Logic Software licensing and marketing costs||H1+(H4*H5)||$0||$180,000||$330,000||$330,000|
|Htr||Madison Logic Software licensing and marketing costs (risk-adjusted)||$0||$198,000||$363,000||$363,000|
Interviewed organizations reported that implementation and maintenance of the Madison Logic platform was user-friendly and did not incur additional costs for employee upkeep. Employees working with the platform were primarily responsible for creating content or management of the campaigns.
Improved alignment between marketing and sales on usage of information from the platform took slightly more time for the organizations to establish. Marketing managers often had to communicate to sales teams how data pulled from the Madison Logic platform could guide the account qualification process. Meanwhile, sales teams took their time to validate the data and become more trusting of the platform. Typically, this communication was carried out over the course of a marketing campaign that piloted the platform.
Marketers seeking to integrate with Marketo required slightly more planning, with some managers citing sales teams needing to be assuaged that Madison Logic would not interfere with account information on Salesforce and how the data would ultimately appear.
For the composite analysis, Forrester assumes:
Two full-time content marketers are dedicated to creating demand generation content and managing display ad campaigns.
One separate full-time sales employee allocates one-third of their time to handling accounts and data taken from the Madison Logic platform, ensuring that salespeople for each account see the information.
Ongoing FTE supports costs will vary based on associated salaries and potential for adding or removing employees based on the scale of campaigns.
To account for these risks, Forrester adjusted this cost upward by 10%, yielding a three-year risk-adjusted total PV of $446,166.
|Ref.||Metric||Calc.||Initial||Year 1||Year 2||Year 3|
|I1||Number of FTE team members dedicated to creating and managing campaigns through Madison Logic||Interviews||2||2||2|
|I2||Number of team members supporting ongoing marketing attribution monitoring and reporting Madison Logic syndication||1||1||1|
|I3||% of supporting FTE bandwidth dedicated to Madison Logic||33%||33%||33%|
|I4||Average FTE salary of members on Madison Logic team||$70,000||$70,000||$70,000|
|It||Ongoing Madison Logic FTE support costs||I1*14+I2*I3*I4||$0||$163,100||$163,100||$163,100|
|Itr||Ongoing Madison Logic FTE support costs (risk-adjusted)||$0||$179,410||$179,410||$179,410|
These risk-adjusted ROI, NPV, and payback period values are determined by applying risk-adjustment factors to the unadjusted results in each Benefit and Cost section.
|Initial||Year 1||Year 2||Year 3||Total||Present Value|
The financial results calculated in the Benefits and Costs sections can be used to determine the ROI, NPV, and payback period for the composite organization’s investment. Forrester assumes a yearly discount rate of 10% for this analysis.
The following information is provided by Madison Logic. Forrester has not validated any claims and does not endorse Madison Logic or its offerings.
Madison Logic empowers B2B marketers to convert their best accounts faster. Its global account-based marketing platform allows marketers to find influencers at their best prospects, engage them during all buying stages, and accelerate their journeys.
Organizations don’t buy B2B products and services; people do. Madison Logic helps you find the key influencers within your target accounts, and it predicts research behavior so you can reach the most valuable audiences on the websites and social media they’re already using.
The ML Platform uses a B2B data management platform (the ML Data Cloud) to connect you with real people in your target accounts. This enables you to build audiences using data science that analyzes multiple data sets — first-party and third-party — to precisely reach B2B buyers based not only on the company they work for but also on the job title, geography, and research activities they’re conducting across the B2B web.
By using Journey Acceleration, powered by the ML Data Cloud, marketers can reach multiple buyers with relevant content to achieve full funnel messaging. The result? Pipeline acceleration and true marketing attribution.
Once you find the right people, the ML Platform empowers you to speed them on their buying journey with the right mix of channels and content. By integrating the ML Data Cloud with your CRM and marketing automation platforms, you can align messaging across every stage of the funnel and combine your nurturing and sales messaging with ML’s content syndication and ABM advertising.
Engage the right people before they raise their hands.
Accelerate buyer journeys — continuously and automatically.
Measure what matters.
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Total Economic Impact is a methodology developed by Forrester Research that enhances a company’s technology decision-making processes and assists vendors in communicating the value proposition of their products and services to clients. The TEI methodology helps companies demonstrate, justify, and realize the tangible value of IT initiatives to both senior management and other key business stakeholders.
Benefits represent the value delivered to the business by the product. The TEI methodology places equal weight on the measure of benefits and the measure of costs, allowing for a full examination of the effect of the technology on the entire organization.
Costs consider all expenses necessary to deliver the proposed value, or benefits, of the product. The cost category within TEI captures incremental costs over the existing environment for ongoing costs associated with the solution.
Flexibility represents the strategic value that can be obtained for some future additional investment building on top of the initial investment already made. Having the ability to capture that benefit has a PV that can be estimated.
Risks measure the uncertainty of benefit and cost estimates given: 1) the likelihood that estimates will meet original projections and 2) the likelihood that estimates will be tracked over time. TEI risk factors are based on “triangular distribution.”
The present or current value of (discounted) cost and benefit estimates given at an interest rate (the discount rate). The PV of costs and benefits feed into the total NPV of cash flows.
The present or current value of (discounted) future net cash flows given an interest rate (the discount rate). A positive project NPV normally indicates that the investment should be made, unless other projects have higher NPVs.
A project’s expected return in percentage terms. ROI is calculated by dividing net benefits (benefits less costs) by costs.
The interest rate used in cash flow analysis to take into account the time value of money. Organizations typically use discount rates between 8% and 16%.
The breakeven point for an investment. This is the point in time at which net benefits (benefits minus costs) equal initial investment or cost.
The initial investment column contains costs incurred at “time 0” or at the beginning of Year 1 that are not discounted. All other cash flows are discounted using the discount rate at the end of the year. PV calculations are calculated for each total cost and benefit estimate. NPV calculations in the summary tables are the sum of the initial investment and the discounted cash flows in each year. Sums and present value calculations of the Total Benefits, Total Costs, and Cash Flow tables may not exactly add up, as some rounding may occur.