The Total Economic Impact™ Of Twilio Segment
Cost Savings And Business Benefits Enabled By Twilio Segment
A Forrester Total Economic Impact™ Study Commissioned By Twilio, August 2024
The foundation of modern marketing is heavily dependent on high quality, timely, and complete customer data. However, challenges such as a fragmented digital ecosystem, technical complexities, and data deprecations continue to hinder effective data utilisation and access. To effectively engage with customers, organisations must prioritise actionable data that can be used across multiple channels. A comprehensive solution that ingests data, offers a comprehensive view of the customer, and activates this data for marketing activities — such as customer insights, personalisation, and channel reach — is essential for enhancing customer experience (CX) and driving success.
Twilio Segment is a customer data platform (CDP) that enables the activation of real-time, first-party customer data across engagement channels. It provides a unified view of the customer, allowing marketing teams to enhance their understanding and focus on robust audience segmentation and personalisation. Engineering teams benefit from improved data quality management and collection, and can thus integrate multiple data sources into downstream tools. This eliminates complex data engineering processes and the need for manual data cleansing. Product teams can leverage this centralised data to drive product improvements and innovation.
Twilio commissioned Forrester Consulting to conduct a Total Economic Impact™ (TEI) study and examine the potential return on investment (ROI) enterprises may realise by deploying Twilio Segment.1 The purpose of this study is to provide readers with a framework to evaluate the potential financial impact of Twilio Segment on their organisations.
Return on investment (ROI)
186%
Net present value (NPV)
$1.19M
To better understand the benefits, costs, and risks associated with this investment, Forrester interviewed the representative of an organisation who has experience using Twilio Segment. Forrester used this experience to project a three-year financial analysis.
Prior to using Twilio Segment, the interviewee’s organisation did not have a CDP solution in place and relied on business analytics tools instead. The organisation was unable to consolidate their customer data, and data that was collected remained fragmented and distributed across multiple channels and various touchpoints. Previous attempts to manage customer data and engagement strategies were unsuccessful, leading to a disjointed view of customer profiles. This limitation hindered their ability to effectively segment audiences and gain insights into individual customer behaviours and preferences.
After the investment in Twilio Segment, the interviewee’s organisation was able to activate their first-party data effectively, enhancing the ability to utilise unified customer profiles across various marketing and operational initiatives. Key results from the investment include considerable incremental profit driven by better customer insights and faster time to market, as well as greater productivity gains from improved data management and analysis efficiency.
Key Findings
Quantified benefits. Three-year, risk-adjusted present value (PV) quantified benefits include:
- Incremental profit enabled by improved customer behaviour insights of $1.39 million. Twilio Segment enables valuable insights into customer interactions on the website by capturing web traffic and real-time user data. This detailed understanding of customer behaviour enables the redesign and relaunch of the website, which improves mobile conversion rates.
- Productivity gains from more efficient data management and analysis of $227,400. Twilio Segment streamlines data integration and automates data export from the warehouse to marketing tools — simplifying processes and accelerating data availability. Additionally, the platform enables rapid audience segmentation without complex coding, enhancing campaign effectiveness.
- Incremental profit realised with faster time to market of $201,100. Twilio Segment’s consistent data collection, processing, and integration methods enable faster deployment of their e-commerce product, significantly reducing time to market and accelerating profit delivery.
Unquantified benefits. Benefits that are not quantified for this study include:
- Improved audience strategy. Twilio Segment’s identity resolution feature creates unified customer profiles from data across various touchpoints, which enhances the effectiveness and personalisation of audience targeting. This makes personalised targeting a crucial growth driver for their B2C division.
- Enhanced data privacy and governance. Twilio Segment improves data privacy and governance by streamlining consent management, ensuring compliance with regulations, and building customer trust. Twilio Segment's capabilities also simplifies schema configuration, which aids the interviewee’s organisation in maintaining analytics compliance.
- Ownership of the tracking and analysis of user interactions. Twilio Segment provides organisations with greater control and precision over defining, tracking, and analysing a web session, which tracks user interactions. Twilio Segment enables the interviewee’s organisation to define sessions based on their specific needs, moving away from relying on the definitions provided by external platforms.
- Unify data management and tracking across different tech stacks. Twilio Segment enables consistent tracking and unifies data management across their consumer brands and recreation operators, regardless of their underlying technology ecosystems (e.g., online retail platform, web application services).
Costs. Three-year, risk-adjusted PV costs for the interviewee’s organisation include:
- Twilio Segment licensing and professional services costs. Adopting Twilio Segment incurs annual recurring licensing and professional services fees, which are dependent on the organisation’s use cases and features. Over three years, these fees add up to a risk-adjusted total PV of $503,700. For an accurate quote on the license and professional services fees, please contact Twilio.
- Internal costs for deployment and maintenance. The interviewee’s organisation requires internal resources across solution deployment and maintenance. The three-year, risk-adjusted value of these costs is $132,400.
The interview and financial analysis found that the representative’s organisation experiences benefits of $1.82 million over three years versus costs of $636,100, adding up to a net present value (NPV) of $1.19 million and an ROI of 186%.
Key Statistics
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Return on investment (ROI)
186%
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Benefits PV
$1.82M
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Net present value (NPV)
$1.19M
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Payback
<6 months
Benefits (Three-Year)
Incremental profit driven by improved customer behaviour insights Productivity gains from more efficient data management and analysis Incremental profit realised with faster time to marketTEI Framework And Methodology
From the information provided in the interviews, Forrester constructed a Total Economic Impact™ framework for those organisations considering an investment in Twilio Segment.
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 Twilio Segment can have on an organisation.
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Due Diligence
Interviewed Twilio stakeholders and Forrester analysts to gather data relative to Twilio Segment.
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Interview
Interviewed the representative of an organisation using Twilio Segment to obtain data with respect to costs, benefits, and risks.
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Financial Model Framework
Constructed a financial model representative of the interview using the TEI methodology and risk-adjusted the financial model based on issues and concerns of the interviewee.
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Case Study
Employed four fundamental elements of TEI in modelling the investment impact: benefits, costs, flexibility, and risks. Given the increasing sophistication of ROI analyses related to IT investments, Forrester’s TEI methodology provides a complete picture of the total economic impact of purchase decisions. Please see Appendix A for additional information on the TEI methodology.
Disclosures
Readers should be aware of the following:
This study is commissioned by Twilio 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 organisations will receive. Forrester strongly advises that readers use their own estimates within the framework provided in the study to determine the appropriateness of an investment in Twilio Segment.
Twilio 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.
Twilio provided the customer name for the interview but did not participate in the interview.
Consulting Team:
Tamira Lee, Zhi Tao Ng
Drivers leading to the Twilio Segment investment
Interviewee’s Organisation
Forrester interviewed the representative of an organisation who has experience using Twilio Segment. Their organisation has the following characteristics:
- Retail recreation organisation headquartered in Australia.
- Has 150 employees.
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Annual organisational revenue of US$100 million.
Key Challenges
Prior to the implementation of Twilio Segment, the organisation solely relied on business analytics tools to provide detailed insights into channel interaction and understand online customer and user analytics behaviour. The interviewee noted how their organisation struggled with:
- A fragmented customer view. The interviewee noted how the lack of a CDP solution in place caused their organisation to have a disjointed understanding of their customers, as they struggled with having siloed first-party customer interaction data across various touchpoints.
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Limited audience insights. The lack of a unified data solution limited their ability to segment audience profiles and gain insights tailored to individual customer behaviours and preferences.
Solution Requirements/Investment Objectives
The interviewee’s organisation searched for a solution that could:
- Easily integrate data across multiple downstream destinations. Twilio Segment simplified the interviewee’s process of connecting to downstream destinations, such as marketing tools and analytics platforms. This ease of integration reduced complexity and streamlined data flow across the organisation’s technology stack. The interviewee also highlighted how Twilio Segment reduced complexity in data integration and collection from multiple analytics tools through a single tag implementation.
- Effectively manage and segment audience profiles. Twilio Segment enabled the interviewee’s organisation to efficiently segment and manage audiences. The solution facilitated advanced audience segmentation, which leveraged identity resolution to consolidate customer activities into unified profiles in real time.
- Activate insights from first-party data. The interviewee mentioned that Twilio Segment allowed their organisation to activate their first-party data effectively, enhancing the ability to utilise unified customer profiles across various marketing and operational initiatives. This provided immediate insights by centralising and analysing data from multiple sources in real time.
Use Case Description
The interviewee is from the retail recreation industry and offers a wide range of experiences to mass consumers and business segments. Previously, they had not implemented a customer data platform and relied on disparate data sources. The organisation needed a customer data platform capable of integrating customer data across their business. The following quantified and unquantified benefits and costs highlight how Twilio Segment was able to drive efficient data management, enhance customer insights, and ultimately drive incremental product improvements and faster time to market for the interviewee’s organisation.
For this use case, Forrester has modelled benefits and costs over three years.
Quantified benefit data
Total Benefits
| Ref. | Benefit | Year 1 | Year 2 | Year 3 | Total | Present Value |
|---|---|---|---|---|---|---|
| Atr | Incremental profit driven by improved customer behaviour insights | $530,989 | $562,159 | $593,181 | $1,686,329 | $1,392,978 |
| Btr | Productivity gains from more efficient data management and analysis | $89,716 | $91,541 | $93,366 | $274,622 | $227,360 |
| Ctr | Incremental profit realised with faster time to market | $79,360 | $80,960 | $82,560 | $242,880 | $201,083 |
| Total benefits (risk-adjusted) | $700,065 | $734,660 | $769,107 | $2,203,832 | $1,821,421 | |
Incremental Profit Driven By Improved Customer Behaviour Insights
Evidence and data. Forrester research showed that despite challenges around data deprecation and a fragmented marketing environment, many firms in APAC continue to rely on CDPs to bridge customer data silos, harness the potential of first-party data, and gain deeper customer insights.2
- The interviewee highlighted that Twilio Segment allowed their organisation to gain valuable insights into customer interactions on their website. By capturing web traffic and real-time user interactions (e.g., page views, clicks, form submissions), the team developed a more granular understanding of customer behaviour, preferences, and tendencies across different engagement channels. Leveraging these insights enabled the team to redesign and relaunch their website, and ultimately improved mobile conversion rates.
Modelling and assumptions. Based on the interview, Forrester assumes the following when building the model:
- An active subscriber base of 500,000 people in Year 1. The number of active subscribers will increase by 2% each year to reach 520,200 in Year 3.
- An average order value of $163 per subscriber in Year 1. The figure will increase by 2% each year to reach $169 by Year 3.
- Each subscriber has an average purchase frequency of 1.22 orders per year. The average purchase frequency will increase by 2% each year to reach 1.26 orders in Year 3.
- By leveraging on the enhanced customer behaviour insights, the organisation sees a 15% improvement in mobile conversion rate of their newly launched website.
- Mobile traffic constitutes 70% of the total traffic footprint of the organisation.
- A solution attribution ratio of 60% isolates the specific impact of Twilio Segment in driving this incremental profit.
- The operating margin is 10%.
Risks. The ability to achieve incremental profit through greater customer behaviour insights can vary due to the differences in the:
- Size of the subscriber base.
- Average order value per subscriber.
- Purchase frequency per subscriber.
- Ability to utilise the insights to improve the conversion rate of engagement channels.
Results. To account for these risks, Forrester adjusted this benefit downward by 15%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $1.4 million.
Incremental Profit Driven By Improved Customer Behaviour Insights
| Ref. | Metric | Source | Year 1 | Year 2 | Year 3 |
|---|---|---|---|---|---|
| A1 | Active subscribers | Interview | 500,000 | 510,000 | 520,200 |
| A2 | Average order value per subscriber | Interview | $163 | $166 | $169 |
| A3 | Average purchase frequency per subscriber | Interview | 1.22 | 1.24 | 1.26 |
| A4 | Improvement in mobile conversion rate of newly launched website, driven by insights from Twilio Segment | Interview | 15% | 15% | 15% |
| A5 | Percentage of mobile traffic footprint | Interview | 70% | 70% | 70% |
| A6 | Solution attribution ratio | TEI standard | 60% | 60% | 60% |
| A7 | Operating margin | TEI standard | 10% | 10% | 10% |
| At | Incremental profit driven by improved customer insights | A1*A2*A3*A4*A5*A6*A7 | $624,693 | $661,364 | $697,860 |
| Risk adjustment | ↓15% | ||||
| Atr | Incremental profit driven by improved customer insights (risk-adjusted) | $530,989 | $562,159 | $593,181 | |
| Three-year total: $1,686,329 | Three-year present value: $1,392,978 | ||||
Productivity Gains From More Efficient Data Management And Analysis
Evidence and data. The interviewee highlighted significant time savings for both data engineers and marketing automation specialists in their data management and customer interaction analysis workflows. These efficiency gains are primarily achieved through:
- Ease of integration of various downstream destinations. Instead of requiring data engineers to create and maintain separate integrations for each downstream destination, Twilio Segment allowed the interviewee’s team to develop a single event integration that served multiple destinations. This consolidation reduced complexity and freed up valuable time for their data engineers to concentrate on core development tasks.
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Simplification of data export from data warehouse to marketing tools. Previously, exporting data from their data warehouse to external marketing platforms was cumbersome for the interviewee’s organisation as they were required to build SQL tables and use a file transfer protocol for data transfer. The interviewee also mentioned how they needed to manually map data from various sources to different marketing tools or analytics platforms.
Twilio Segment eliminated this complex export step by automating and streamlining the event-to-destination mapping workflow. This ensured consistent and accurate data routing across platforms, saving valuable time for the interviewee’s team. Twilio Segment also provided direct integrations and APIs, which enabled seamless and efficient data flow between systems. This improvement reduced operational overhead and accelerated data availability for marketing campaigns. - Greater efficiency in building audience segments. By eliminating the need for SQL expertise, Twilio Segment empowered the interviewee’s marketing team to swiftly create audience segments without complex coding. This shift empowered teams to easily deploy targeted campaigns based on real-time insights, enhancing operational agility and campaign effectiveness.
Modelling and assumptions. Based on the interview, Forrester assumes the following when building the model:
- The team involves four data engineers and three marketing automation specialists.
- Data engineers save 30% of working hours per year exporting data/maintaining integration codes.
- Marketing automation specialists save 25% of working hours per year building audiences.
- The average fully-burdened hourly salary of a data engineer is $53 in Year 1, and increases by 2% year over year to $55 in Year 3.
- The average fully-burdened hourly salary of a marketing automation specialist is $43 in Year 1, and increases by 2% year over year to $45 in Year 3.
- The productivity recapture rate, or the percentage of the total time saved that is used by employees to drive value, is 50%.
Risks. The productivity gains from more efficient data management and analysis can vary across organisations due to the differences in:
- Number of data engineers and marketing automation specialists involved in maintaining integration codes and building audiences.
- Productivity of data engineers and marketing automation specialists.
- Salary of data engineers and marketing automation specialists.
- Data management and analysis processes.
Results. To account for these risks, Forrester adjusted this benefit downward by 10%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $227,400.
Productivity Gains From More Efficient Data Management And Analysis
| Ref. | Metric | Source | Year 1 | Year 2 | Year 3 | |||
|---|---|---|---|---|---|---|---|---|
| B1 | Data engineers | Interview | 4 | 4 | 4 | |||
| B2 | Percentage of working hours saved by data engineers annually on exporting data and maintaining integration codes | Interview | 30% | 30% | 30% | |||
| B3 | Subtotal: Time saved on exporting and maintaining integration codes (hours) | A1*A2*2080 | 2,496 | 2,496 | 2,496 | |||
| B4 | Marketing automation specialists | Interview | 3 | 3 | 3 | |||
| B5 | Percentage of working hours saved by marketing automation specialists annually on building audiences with Twilio Segment | Interview | 25% | 25% | 25% | |||
| B6 | Subtotal: Time saved on building audiences (hours) | B4*B5*2080 | 1,560 | 1,560 | 1,560 | |||
| B7 | Average fully-burdened hourly salary of a data engineer | TEI standard | $53 | $54 | $55 | |||
| B8 | Average fully-burdened hourly salary of a marketing automation specialist | TEI standard | $43 | $44 | $45 | |||
| B9 | Productivity factor | TEI standard | 50% | 50% | 50% | |||
| Bt | Productivity gains from more efficient data management and analysis | B9*[(B3*B7)+(B6*B8)] | $99,684 | $101,712 | $103,740 | |||
| Risk adjustment | ↓10% | |||||||
| Btr | Productivity gains from more efficient data management and analysis (risk-adjusted) | $89,716 | $91,541 | $93,366 | ||||
| Three-year total: $274,622 | Three-year present value: $227,360 | |||||||
Incremental Profit Realised With Faster Time To Market
Evidence and data. The interviewee highlighted how Twilio Segment significantly improved their organisation’s ability and speed to bring e-commerce product solutions to market through a consistent method for data collection, processing, and integration.
For greater context, the interviewee mentioned that one of their business streams involved supporting smaller businesses in the retail recreation industry, with plug-and-play features for marketing, distribution, and technology. Twilio Segment streamlined the integration of data into marketing ecosystems, allowing their client to quickly transfer data from their booking engine into their marketing platform. This efficiency enabled faster utilisation of the plug-and-play booking engine feature, which significantly reduced the time to market. This enhancement resulted in notable business benefits, including incremental profit through faster deployment and customer usage.
Modelling and assumptions. Based on the interview, Forrester assumes the following when building the model:
- The average annual revenue gained from their e-commerce solutions business is $9.9 million in Year 1, which increases by 2% year over year to $10.3 million in Year 3.
- A 17% revenue gain is attributed to faster time to market for delivering the plug-and-play ecommerce solution for clients.
- A solution attribution ratio of 60% isolates the specific impact of Twilio Segment in driving faster time to market.
- The operating margin is 10%.
Risks. The incremental profit realised with faster time to market can vary across organisations due to differences in:
- Average revenue of the ecommerce solutions business.
- Efficiency of integrating data into marketing ecosystems.
Results. To account for these risks, Forrester adjusted this benefit downward by 20% yielding a three-year, risk-adjusted total PV (discounted at 10%) of $201,100.
Incremental Profit Realised With Faster Time To Market
| Ref. | Metric | Source | Year 1 | Year 2 | Year 3 |
|---|---|---|---|---|---|
| C1 | Average annual revenue through their e-commerce solutions business |
Interview | $9,920,000 | $10,120,000 | $10,320,000 |
| C2 | Percentage of revenue gained attributed to faster time to market for client data sharing with Twilio Segment | Interview | 17% | 17% | 17% |
| C3 | Solution attribution ratio | TEI standard | 60% | 60% | 60% |
| C4 | Operating margin | TEI standard | 10% | 10% | 10% |
| Ct | Incremental profit realised with faster time to market | C1*C2*C3*C4 | $99,200 | $101,200 | $103,200 |
| Risk adjustment | ↓20% | ||||
| Ctr | Incremental profit realised with faster time to market (risk-adjusted) | $79,360 | $80,960 | $82,560 | |
| Three-year total: $242,880 | Three-year present value: $201,083 | ||||
Unquantified Benefits
The interviewee mentioned the following additional benefits that the organisation experienced but was not able to quantify.
- Improved audience strategy. Relying on Twilio Segment allowed for greater effectiveness and personalisation in audience targeting and marketing messaging. Twilio Segment’s identity resolution feature stitched together data from known and unknown users across various touchpoints in the ecosystem, which created unified customer profiles and enabled a comprehensive understanding of their customers. The interviewee highlighted how their organisation was able to develop targeted action plans for social media, empowering personalised targeting to be a key growth pillar for their organisation’s B2C division.
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Enhanced data privacy and governance. Twilio Segment's robust data management capabilities increased organisational readiness for impending privacy changes, which ensured their compliance with data privacy regulations and respect for user preferences and consent. The interviewee emphasised how Twilio Segment streamlined consent management and facilitated the right to be forgotten (RTBF) within their organisation. This approach not only maintained legal compliance but also built trust with customers.
- The interviewee highlighted how Twilio Segment streamlined schema configuration and data management to maintain analytics compliance and standards, “I knew that Twilio Segment could handle the complexity of configuring our ecommerce tracking schema to meet the requirements of our new analytics platform.”
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Ownership of tracking and analysis of user interactions. Adopting Twilio Segment allowed for greater control and precision over how user interactions were tracked and analysed. The interviewee highlighted, “We had a high reliance on our external platforms’ definition of a web session interaction, and we wanted to take ownership of that session definition with Twilio Segment.” Twilio Segment helped to define what constituted a user session based on their specific business needs and user behaviour, which ensured that session tracking aligned with their goals and reporting requirements.
Flexibility
The value of flexibility is unique to each customer. There are multiple scenarios in which a customer might implement Twilio Segment and later realise additional uses and business opportunities, including:
- The ability to integrate new downstream data destinations and sources. Twilio Segment offers a wide range of native integrations and partner ecosystem — the interviewee highlighted how its modularity feature allowed their organisation to seamlessly onboard and integrate new sources and downstream destination platforms into their organisation’s existing customer data management capabilities. This offered them the flexibility to efficiently scale data operations and incorporate innovative data sources in tandem with their target audience’s and marketing team’s shifting preferences.
- Greater access to data. Twilio Segment's capabilities integrated a vast amount of data from various engagement channels, which allowed marketers to gain a comprehensive understanding of their customers and manage multichannel campaigns more effectively. The interviewee noted, “I could have 10 A/B platforms running tomorrow almost overnight, and I could send data into any BI [business intelligence] platform and get insights immediately.” This scalable data integration enabled the interviewee’s organisation to adapt and enhance their CX, continually improving their strategies based on real-time insights.
Flexibility would also be quantified when evaluated as part of a specific project (described in more detail in Appendix A).
Quantified cost data
Total Costs
| Ref. | Cost | Initial | Year 1 | Year 2 | Year 3 | Total | Present Value |
|---|---|---|---|---|---|---|---|
| Dtr | Twilio Segment licensing and professional services costs | $66,000 | $176,000 | $176,000 | $176,000 | $594,000 | $503,686 |
| Etr | Internal costs for deployment and maintenance | $54,855 | $30,545 | $31,231 | $31,918 | $148,548 | $132,414 |
| Total costs (risk-adjusted) | $120,855 | $206,545 | $207,231 | $207,918 | $742,548 | $636,100 | |
Twilio Segment Licensing And Professional Services Costs
Evidence and data. The interviewee’s organisation incurred annual recurring licensing and professional services fees for Twilio Segment, which were typically incurred for the deployment of the solution. The total annual fees depended on the organisation’s use cases and features. For an accurate quote on the license and professional services fees, please contact Twilio.
Modelling and assumptions. Based on the interview, Forrester assumes the following when building the model:
- The initial professional services cost per year is $60,000.
- The annual licensing cost is $160,000 across three years.
Risks. This cost calculation can vary across organisations due to differences in:
- Professional services fee incurred.
- Custom licensing costs.
- Type and number of licenses purchased.
Results. To account for these risks, Forrester adjusted this cost upward by 10%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $503,700.
Twilio Segment Licensing And Professional Services Costs
| Ref. | Metric | Source | Initial | Year 1 | Year 2 | Year 3 |
|---|---|---|---|---|---|---|
| D1 | Annual licensing costs | Interview | $160,000 | $160,000 | $160,000 | |
| D2 | Professional services costs | Interview | $60,000 | $0 | $0 | $0 |
| Dt | Twilio Segment licensing and professional services costs | D1+D2 | $60,000 | $160,000 | $160,000 | $160,000 |
| Risk adjustment | ↑10% | |||||
| Dtr | Twilio Segment licensing and professional services costs (risk-adjusted) | $66,000 | $176,000 | $176,000 | $176,000 | |
| Three-year total: $594,000 | Three-year present value: $503,686 | |||||
Internal Costs For Deployment And Maintenance
Evidence and data. The interviewee’s organisation incurred costs and effort across solution deployment and maintenance during the implementation process for Twilio Segment. The total deployment and maintenance cost were based on the complexity and size of the user team, implementation approach, data source, data destination, technical specifications.
Modelling and assumptions. This section explains how the modelling is done.
- The deployment phase involves one front-end engineer manager, one marketing automation specialist, and one product owner who are usually the product’s point of contacts and oversee end users. Deployment takes place over a period of six months and requires 35% of each of these employees’ time.
- The average fully-burdened hourly salary of a front-end engineer is $46 in Year 1, which increases by 2% year over year to $48 in Year 3.
- The average fully-burdened hourly salary of a marketing automation specialist is $43 in Year 1, which increases by 2% year over year to $45 in Year 3.
- The average fully-burdened hourly salary of a product owner is $48 in Year 1, which increases by 2% year over year to $50 in Year 3.
- The maintenance phase involves one front-end engineer manager and one marketing automation specialist. Solution maintenance requires 15% of each of their time and takes place across three years.
Risks. The total internal costs for deployment and maintenance may differ across organisations due to variances in:
- Number of employees and their functions required to deploy the solution.
- Number of employees and their functions required to maintain the solution.
- Amount of time dedicated to solution deployment and maintenance.
- The average fully-burdened hourly salary of a front-end engineer, marketing automation specialist, and product owner.
Results. To account for these risks, Forrester adjusted this cost upward by 10%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $132,400.
Internal Costs For Deployment And Maintenance
| Ref. | Metric | Source | Initial | Year 1 | Year 2 | Year 3 |
|---|---|---|---|---|---|---|
| E1 | Months spent on solution deployment | Interview | 6 | 0 | 0 | 0 |
| E2 | Percentage of working hours spent on solution deployment | Interview | 35% | 0% | 0% | 0% |
| E3 | Front-end engineers required for solution deployment | Interview | 1 | 0 | 0 | 0 |
| E4 | Marketing automation specialists required for solution deployment | Interview | 1 | 0 | 0 | 0 |
| E5 | Product owners required for solution deployment | Interview | 1 | 0 | 0 | 0 |
| E6 | Average fully-burdened hourly salary of a front-end engineer | TEI standard | $46 | $46 | $47 | $48 |
| E7 | Average fully-burdened hourly salary of a marketing automation specialist | TEI standard | $43 | $43 | $44 | $45 |
| E8 | Average fully-burdened hourly salary of a product owner | TEI standard | $48 | $48 | $49 | $50 |
| E9 | Solution deployment costs incurred by front-end engineers | (E1/12)*E2*2080 *E3*E6 | $16,744 | $0 | $0 | $0 |
| E10 | Solution deployment costs incurred by marketing automation specialists | (E1/12)*E2*2080 *E3*E7 | $15,652 | $0 | $0 | $0 |
| E11 | Solution deployment costs incurred by product owners | (E1/12)*E2*2080 *E3*E8 | $17,472 | $0 | $0 | $0 |
| E12 | Subtotal: Solution deployment costs | E9+E10+E11 | $49,868 | $0 | $0 | $0 |
| E13 | Percentage of working hours spent on solution maintenance annually | Interview | 0% | 15% | 15% | 15% |
| E14 | Front-end engineers required for ongoing maintenance | Interview | 0 | 1 | 1 | 1 |
| E15 | Marketing automation specialists required for ongoing maintenance | Interview | 0 | 1 | 1 | 1 |
| E16 | Solution maintenance costs incurred by front-end engineers | E9*E13*2080 | $0 | $14,352 | $14,664 | $14,976 |
| E17 | Solution maintenance costs incurred by marketing automation specialists | E10*E13*2080 | $0 | $13,416 | $13,728 | $14,040 |
| E18 | Subtotal: Solution maintenance costs | E16+E17 | $0 | $27,768 | $28,392 | $29,016 |
| Et | Total internal costs for deployment and maintenance | E12+E18 | $49,868 | $27,768 | $28,392 | $29,016 |
| Risk adjustment | ↑10% | |||||
| Etr | Total internal costs for deployment and maintenance (risk-adjusted) | $54,855 | $30,545 | $31,231 | $31,918 | |
| Three-year total: $148,548 | Three-year present value: $132,414 | |||||
Consolidated Three-Year Risk-Adjusted Metrics
Cash Flow Chart (Risk-Adjusted)
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The financial results calculated in the Benefits and Costs sections can be used to determine the ROI, NPV, and payback period for the organisation’s investment. Forrester assumes a yearly discount rate of 10% for this analysis.
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.
Cash Flow Analysis (Risk-Adjusted Estimates)
| Initial | Year 1 | Year 2 | Year 3 | Total | Present Value | |
|---|---|---|---|---|---|---|
| Total costs | ($120,855) | ($206,545) | ($207,231) | ($207,918) | ($742,548) | ($636,100) |
| Total benefits | $0 | $700,065 | $734,660 | $769,107 | $2,203,832 | $1,821,421 |
| Net benefits | ($120,855) | $493,520 | $527,429 | $561,189 | $1,461,283 | $1,185,321 |
| ROI | 186% | |||||
| Payback period (months) | Less than 6 | |||||
Appendix A: Total Economic Impact
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 realise the tangible value of IT initiatives to both senior management and other key business stakeholders.
Total Economic Impact Approach
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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 organisation.
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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.
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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.
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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 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.
Appendix B: Endnotes
1 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.
2 Source: The Customer Data Platforms In Asia Pacific Landscape, Q1 2024, Forrester Research Inc., January 24, 2024.
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