Total Economic Impact
Cost Savings And Business Benefits Enabled By Google Cloud Customer Engagement Suite With Google AI
A FORRESTER TOTAL ECONOMIC IMPACT STUDY COMMISSIONED BY Google Cloud, May 2025
Total Economic Impact
A FORRESTER TOTAL ECONOMIC IMPACT STUDY COMMISSIONED BY Google Cloud, May 2025
Customer experience is crucial to firms’ ability to win, serve, and retain customers, but they have found it challenging to deliver. Advances in automation, conversational and generative AI, and agent assist tools provide new opportunities to deliver better customer experiences while also improving employee productivity and agent experiences and decreasing labor costs —leading to better business outcomes.1
Google Cloud Customer Engagement Suite with Google AI is an end-to-end application combining conversational AI products with optional omnichannel contact-center-as-a-service (CCaaS) functionality. This Google AI solution includes Conversational Agents (IVA), Agent Assist, and Conversational Insights. It provides the ability to leverage both deterministic and generative AI (genAI) capabilities simultaneously.
Google Cloud commissioned Forrester Consulting to conduct a Total Economic Impact™ (TEI) study and examine the potential return on investment (ROI) enterprises may realize by deploying Google Cloud Customer Engagement Suite with Google AI.2 The purpose of this study is to provide readers with a framework to evaluate the potential financial impact of Google Cloud Customer Engagement Suite with Google AI on their organizations.
To better understand the benefits, costs, and risks associated with this investment, Forrester interviewed four decision-makers and surveyed 160 respondents with experience using Google Cloud Customer Engagement Suite with Google AI. For the purposes of this study, Forrester aggregated the experiences of the interviewees and survey respondents and combined the results into a single composite organization, which is a B2C services company with 6,000 global contact center agents and $10 billion in annual revenue.
Interviewees said that prior to using Google Cloud Customer Engagement Suite with Google AI, their organizations leveraged different contact routing and automation solutions, including intelligent virtual assistants (IVAs), for different channels. These fragmented solutions were difficult to manage and scale and led to poor customer experiences.
After the investment in Google Cloud Customer Engagement Suite with Google AI, the interviewees were able to consolidate and scale their solutions across the organization. Key results from the investment include increased contact containment rates, agent efficiencies, increased revenue, and improved customer experience.
Quantified benefits. Three-year, risk-adjusted present value (PV) quantified benefits for the composite organization include:
Contact containment of 40% in Year 1, increasing to 55% by Year 3, with Conversational Agents. The composite organization’s prior IVA solution contains 30% of contacts. Better intent detection, deployment across multiple channels, and the ability to add and adjust use cases to meet customer needs lead to improved contact containment rates with Google Cloud’s Conversational Agents. Over three years, this increase in contact containment is worth $21.6 million to the composite organization.
Improved interaction efficiency through automated task completion, saving 120 seconds per contact in Year 1, increasing to 130 seconds by Year 3. The live agents who support contacts see time savings on activities like contact authentication, searching for information during the contact, and contact summarization. Over three years, this benefit is worth $8.7 million to the composite organization.
Increased operating income from better routing and information, with $2.0 million in additional revenue in Year 1, doubling to $4.0 million in additional revenue by Year 3. The combination of solutions in Google Cloud Customer Engagement Suite with Google AI provides better information about why customers are contacting support and ensures customers reach the right place — whether that’s a virtual agent or a live agent — more quickly. Agents are better able to meet customers’ needs and better equipped to engage in cross-selling and upselling activities. Over three years, this benefit is worth $584,000 in operating income to the composite organization.
Legacy environment savings from retiring previous solutions. As the composite organization deploys and expands its use of Google Cloud Customer Engagement Suite with Google AI, it is able to retire legacy solutions and associated overhead management costs. Over three years, this benefit is worth $25.5 million to the composite organization.
Unquantified benefits and flexibilities. Benefits that provide value for the composite organization but are not quantified for this study include:
Improved decision-making. Google Cloud Customer Engagement Suite with Google AI allows the composite organization to better understand why customers are contacting them, enabling them to improve customer resources and policies and thus improving the customer experience.
Improved scalability and organizational agility. Google Cloud Customer Engagement Suite with Google AI provides the ability to try out new technologies, adjust use cases, and expand quickly and with relatively low costs, enabling organizations to innovate and meet changing business needs.
Reduced agent training time and managerial overhead. Over time, agent training and ramp-up time may decrease due to automated activities and improved agent support with Agent Assist, while managers might save time through improved quality systems.
Future benefits with generative AI. Google Cloud’s continued investment in generative AI is expected to continue adding new value for the composite organization.
Costs. Three-year, risk-adjusted PV costs for the composite organization include:
Fees paid to Google Cloud. The composite organization pays Google Cloud for artificial intelligence, Conversational Agents for voice and chat, Agent Assist, and professional services. This costs the composite organization $15.6 million over three years.
Implementation, ongoing management, and training costs. Initial implementation takes six months and includes integration with key systems, use case development, and deployment as well as training. Implementation has an upfront cost of $647,000. Ongoing management includes system support and the continued development of use cases and changes to support ongoing business needs, costing the composite organization $857,000 per year. The total costs of implementation, ongoing management, and training for the composite organization are $2.8 million over three years.
The financial analysis that is based on the interviews and survey found that a composite organization experiences benefits of $56.4 million over three years versus costs of $18.4 million, adding up to a net present value (NPV) of $38.0 million and an ROI of 207%.
Return on investment (ROI)
Benefits PV
Net present value (NPV)
| Title | Industry | Geography | Annual revenue | Contact center agents |
|---|---|---|---|---|
| Senior director of engineering | Cybersecurity | Global | $3.5 billion | 2,000 |
| Director of AI operations | Travel | Europe | $250 million | 1,000 |
| Director of AI data and analytics | Telco | Global | $15 billion | 10,000 |
| Senior executive of software development | Consumer services | Global | $135 billion | 50,000 |
Prior to deploying Google Cloud Customer Engagement Suite with Google AI, interviewees’ organizations leveraged different IVA and IVR solutions, typically with different vendors for different channels. They had not deployed any AI-based agent assistive technologies.
Interviewees and survey respondents noted how their organizations struggled with common challenges, including:
Fragmented solutions that were labor-intensive to manage. Because different channels had different solutions in place, each system needed its own use cases, conversation flows, and routing; each required separate maintenance and management activities.
Difficulty with scaling. The fragmented nature of the solutions made it very difficult to scale because of labor costs and the lack of integration across channels and systems. Interviewees also noted that this system left their organizations stuck: Moving off a solution would mean having to rebuild all the conversation flows and system logic.
Poor customer experience. As a result, interviewees said they struggled to provide good customer experiences. Contact routing was inadequate, while containment rates suffered as customers opted out of the existing IVA to try to talk to an agent. Interviewees said their organizations weren’t able to understand customers’ needs and goals — and didn’t see a meaningful path forward with the solutions they had in place.
The interviewees and survey respondents searched for a solution that could:
Scale across channels and use cases. Interviewees noted that with Google Cloud Customer Engagement Suite with Google AI, their teams could design a conversation flow once and deploy it across multiple channels where appropriate. They could use Google Cloud to automatically generate audio rather than manually recording it. And they could integrate with other solutions as needed.
Provide flexibility to solve evolving business needs. Interviewees expected that the scalability and relative ease of Google Cloud Customer Engagement Suite with Google AI compared with prior solutions would provide the flexibility to add and change use cases and quickly address customers’ needs.
Improve the customer experience. Interviewees hoped that better scalability and flexibility combined with better data and new AI capabilities would allow their organizations to understand their customers in ways they hadn’t been able to previously and provide an improved customer experience.
Base: 160 decision-makers for contact centers
Source: A commissioned study conducted by Forrester Consulting on behalf of Google Cloud, April 2025
Based on the interviews and survey, Forrester constructed a TEI framework, a composite company, and an ROI analysis that illustrates the areas financially affected. The composite organization is representative of the interviewees’ organizations, and it is used to present the aggregate financial analysis in the next section. The composite organization has the following characteristics:
Description of composite. The composite organization is a global B2C services company with $10 billion in annual revenue. Its 6,000 contact center agents are globally distributed, with the majority in lower-cost locations and a subset in North America; they support 24 million inbound contacts per year. While agents primarily provide support services, they are able to engage in selling when the opportunity arises.
Deployment characteristics. After a six-month implementation, the composite organization deploys Google Cloud’s Conversational Agents for voice and chat as well as Agent Assist. Adoption increases from Year 1 to Year 3 as new use cases are identified and implemented.
$10 billion annual revenue
6,000 contact center agents
24 million annual contacts between voice and chat
900-second average handle time
Conversational Agents and Agent Assist deployed
| Ref. | Benefit | Year 1 | Year 2 | Year 3 | Total | Present Value |
|---|---|---|---|---|---|---|
| Atr | Contact containment with Conversational Agents | $4,860,000 | $9,720,000 | $12,150,000 | $26,730,000 | $21,579,715 |
| Btr | Improved interaction efficiency through automated task completion | $3,888,000 | $3,375,003 | $3,159,000 | $10,422,003 | $8,697,207 |
| Ctr | Incremental operating income from improved information and routing | $160,000 | $240,000 | $320,000 | $720,000 | $584,222 |
| Dtr | Legacy environment savings | $9,000,000 | $10,350,000 | $11,700,000 | $31,050,000 | $25,525,920 |
| Total benefits (risk-adjusted) | $17,908,000 | $23,685,003 | $27,329,000 | $68,922,003 | $56,387,064 |
Evidence and data. Prior to deploying Google Cloud’s Conversational Agents, interviewees’ organizations leveraged a mix of IVA and IVR solutions, typically with different solutions for different channels. As a result, the solutions weren’t always deployed broadly or consistently. With Google Cloud’s Conversational Agents, interviewees said their organizations were able to deploy the same experience across channels. They were also able to easily scale the solution and add new use cases as they better understood their customers’ needs.
A senior executive of software development at a consumer services organization explained that Google Cloud’s intent detection before the call allowed them to route customers either to a Conversational Agent or to an appropriate live agent, bypassing cumbersome and unhelpful menus. This reduced the number of customers who opted out of automation, improving containment rates.
Interviewees said their organizations’ containment rates in their prior environments ranged from 0% to 35%, depending on the channel and use case.
After deploying Google Cloud’s Conversational Agents, interviewees reported containment rates of 20% to 70%, depending on the channel and use case. All interviewees reported higher containment rates with Google Cloud’s Conversational Agents than with their previous solutions, typically with higher containment rates for chat than voice.
Among survey respondents, 59% indicated they had increased containment rates with Google Cloud Customer Engagement Suite with Google AI, from an average of 42% to almost 54%.
Contact containment rate (blended voice and chat) for the composite organization in Year 3
Modeling and assumptions. Based on the interviews and survey, Forrester assumes the following about the composite organization:
The composite organization receives 24 million inbound contacts per year. These contacts are distributed between voice and chat.
In the prior state, the organization’s existing IVA contains an average of 30% of inbound contacts between voice and chat, resulting in 16.8 million contacts reaching live agents.
With Google Cloud’s Conversational Agents, an average of 40% of contacts are contained between voice and chat in Year 1, increasing to 50% in Year 2 and 55% in Year 3, as new use cases are identified and deployed. This results in 14.4 million chats reaching live agents in Year 1, 12.0 million in Year 2, and 10.8 million in Year 3.
These containment rates are an average, as chat contacts typically have a higher containment rate than voice.
The average handle time for these contacts is 900 seconds.
The average fully burdened hourly rate per live agent is $9.00. A majority of these agents are in lower-cost regions globally, with a subset in North America.
Risks. An organization’s realization of benefits related to contact containment with Conversational Agents will depend upon a variety of factors, including:
The channels and use cases for which the Conversational Agents are deployed.
The nature of user contacts, including the complexity and repeatability of contact topics.
The time and effort an organization dedicates to maintaining, tuning, and expanding use cases for Conversational Agents.
The cost per contact for live agents versus Conversational Agents.
Any existing solutions in place and how effective they are at addressing customer needs.
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 $21.6 million.
| Ref. | Metric | Source | Year 1 | Year 2 | Year 3 | |
|---|---|---|---|---|---|---|
| A1 | Total contacts in legacy environment | Composite | 24,000,000 | 24,000,000 | 24,000,000 | |
| A2 | Containment rate in legacy environment | Interviews and survey | 30% | 30% | 30% | |
| A3 | Contacts handled by live agents in legacy environment | A1*(1-A2) | 16,800,000 | 16,800,000 | 16,800,000 | |
| A4 | Containment rate with Google Cloud Conversational Agents | Interviews and survey | 40% | 50% | 55% | |
| A5 | Contacts handled by live agents with Google Cloud Conversational Agents | A1*(1-A4) | 14,400,000 | 12,000,000 | 10,800,000 | |
| A6 | Additional contacts contained by Google Cloud Conversational Agents | A3-A5 | 2,400,000 | 4,800,000 | 6,000,000 | |
| A7 | Average handle time (AHT) in legacy environment (seconds) | Composite | 900 | 900 | 900 | |
| A8 | Time saved from contact containment (hours) | A6*A7/3,600 seconds per hour | 600,000 | 1,200,000 | 1,500,000 | |
| A9 | Average fully burdened hourly rate per agent | Composite | $9.00 | $9.00 | $9.00 | |
| At | Contact containment with Conversational Agents | A8*A9 | $5,400,000 | $10,800,000 | $13,500,000 | |
| Risk adjustment | ↓10% | |||||
| Atr | Contact containment with Conversational Agents (risk-adjusted) | $4,860,000 | $9,720,000 | $12,150,000 | ||
| Three-year total: $26,730,000 | Three-year present value: $21,579,715 | |||||
Evidence and data. Not all contacts could be handled by intelligent virtual assistants, but interviewees said live agents using AI solutions at their organizations benefitted from time savings on routine, repetitive tasks before, during, and after customer contacts.
The most common areas of time savings reported by interviewees and survey respondents were customer authentication by Conversational Agents, support when searching for relevant information during contacts, and call summarization with Agent Assist after the contact.
Time savings for authentication ranged from 30 to 120 seconds, while call summarization typically saved around 60 seconds.
Time saved per live agent contact by Year 3
Modeling and assumptions. Based on the interviews and survey, Forrester assumes the following about the composite organization:
After containment with Google Cloud’s Conversational Agents, 14.4 million contacts reach live agents in Year 1, decreasing to 12.0 million in Year 2 and 10.8 million in Year 3. These contacts are a mix of voice and chat.
While these contacts are not fully contained, they can be verified by Conversational Agents before reaching a live agent, saving interaction time. In addition, Agent Assist helps agents access relevant information during the contact more quickly and provides call summaries following the contact, further reducing interaction and post-call work times. The total time savings across these activities is an average of 120 seconds per contact in Year 1, increasing to 125 seconds in Year 2 and 130 seconds in Year 3 as the organization expands its use of Agent Assist to support agents during contacts.
The average fully burdened hourly rate per live agent is $9.00. A majority of these agents are in lower-cost regions globally, with a subset in North America.
Risks. An organization’s realization of benefits related to interaction efficiency through automated task completion will depend upon a variety of factors, including:
The use cases and scope of deployment for Conversational Agents, Agent Assist, and any other Google Cloud Customer Engagement Suite with Google AI solutions.
Any existing solutions in place and how effective they are at addressing customer needs.
The time live agents spend on activities such as contact authentication, contact summarization, or searching for information during contacts.
The cost per minute of live agents.
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 $8.7 million.
| Ref. | Metric | Source | Year 1 | Year 2 | Year 3 | |
|---|---|---|---|---|---|---|
| B1 | Contacts handled by live agents after containment by Conversational Agents | A5 | 14,400,000 | 12,000,000 | 10,800,000 | |
| B2 | Interaction time savings from automation with Google Cloud Customer Engagement Suite with Google AI (seconds) | Interviews and survey | 120 | 125 | 130 | |
| B3 | Time saved from automation (hours) | B1*B2/3,600 seconds per hour | 480,000 | 416,667 | 390,000 | |
| B4 | Fully burdened hourly rate per agent | Composite | $9.00 | $9.00 | $9.00 | |
| Bt | Improved interaction efficiency through automated task completion | B3*B4 | $4,320,000 | $3,750,003 | $3,510,000 | |
| Risk adjustment | ↓10% | |||||
| Btr | Improved interaction efficiency through automated task completion (risk-adjusted) | $3,888,000 | $3,375,003 | $3,159,000 | ||
| Three-year total: $10,422,003 | Three-year present value: $8,697,207 | |||||
Evidence and data. Prior to deploying Google Cloud Customer Engagement Suite with Google AI, interviewees’ organizations suffered from poor customer experience in contact centers. Calls weren’t routed to the most appropriate agents or teams, information wasn’t carried through the various interactions, and customers’ needs weren’t being met. After switching to Google Cloud Customer Engagement Suite with Google AI, interviewees and survey respondents reported better routing, intent identification, and customer experiences — and, ultimately, increased revenue.
A senior director of engineering at a cybersecurity organization shared that its telesales had increased significantly, due in part to better contact routing with Conversational Agents.
A director of AI data and analytics at a telco organization said that their company saw increased revenue from improved sales bridging as well as follow-up campaigns. They also reduced revenue leakage due to better compliance with company policies informed by better contact data.
Among survey respondents, 67% said their organization had increased customer retention with Google Cloud Customer Engagement Suite with Google AI, from an average of 44% before to 55% after.
Additionally, 65% of survey respondents said their organization had increased cross-sell revenue and 62% said they increased upsell revenue, with an average total increase of $300,000 per year in revenue between them. Further, 64% of survey respondents reported increased average order values, 62% reported increased conversion rates, and 55% noted increased repeat purchases.
Forrester’s research shows that a customer’s experience with contact centers has an enormous impact on their perception of customer experience quality and that good customer service can deliver massive revenue gains. Customers want service reps to be able to answer their questions on the first contact without needing a supervisor to intervene. Getting customers to the right agent quickly and addressing their problem then and there is key.3 Across survey respondents, 84% reported improved customer satisfaction with Google Cloud Customer Engagement Suite with Google AI, with 73% agreeing or strongly agreeing they saw improved customer satisfaction scores; 86% saw improved first-call resolution; 76% reported reduced average speed of answer; and 55% saw reduced transfer rates.
Other areas where a majority of respondents saw improvements with Google Cloud Customer Engagement Suite with Google AI compared to their prior solution were call routing, intent identification, contact quality, and post-contact survey results.
Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:
The composite organization’s annual revenue is $10 billion per year.
Supported by better routing and Agent Assist, live agents engage in more frequent and more effective cross-selling and upselling and better adhere to corporate policies, leading to an increase in revenue of 0.02% in Year 1 (worth $2 million), 0.03% in Year 2 (worth $3 million), and 0.04% in Year 3 (worth $4 million).
The composite organization’s operating margin is 10%.
Risks. An organization’s realization of benefits related to incremental operating income from improved information and routing will depend upon a variety of factors, including:
The channels and use cases for which Google Cloud Customer Engagement Suite with Google AI solutions is deployed.
The nature of user contacts, including the complexity and repeatability of contact topics.
The time and effort an organization dedicates to maintaining, tuning, and expanding use cases for Google Cloud Customer Engagement Suite with Google AI solutions.
An organization’s industry, products, sales motions, and customer buying behaviors.
Whether and how an organization’s support agents are able to engage in selling activities with customers.
Any existing solutions in place and how effective they are at addressing customer needs.
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 $584,000.
| Ref. | Metric | Source | Year 1 | Year 2 | Year 3 | |
|---|---|---|---|---|---|---|
| C1 | Annual revenue | Composite | $10,000,000,000 | $10,000,000,000 | $10,000,000,000 | |
| C2 | Revenue increase attributable to Google Cloud Customer Engagement Suite with Google AI | Interviews and survey | 0.02% | 0.03% | 0.04% | |
| C3 | Net new revenue attributable to Google Cloud Customer Engagement Suite with Google AI | C1*C2 | $2,000,000 | $3,000,000 | $4,000,000 | |
| C4 | Operating margin | Research data | 10% | 10% | 10% | |
| Ct | Incremental operating income from improved information and routing | C3*C4 | $200,000 | $300,000 | $400,000 | |
| Risk adjustment | ↓20% | |||||
| Ctr | Incremental operating income from improved information and routing (risk-adjusted) | $160,000 | $240,000 | $320,000 | ||
| Three-year total: $720,000 | Three-year present value: $584,222 | |||||
Evidence and data. Interviewees said their organizations were able to retire previous solutions as they rolled out Google Cloud Customer Engagement Suite with Google AI.
Interviewees shared that they were able to eliminate licensing and overhead costs associated with previous solutions.
Savings often increased over time as interviewees expanded their use of Google Cloud and replaced more solutions.
Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:
The composite organization previously deploys other IVA and IVR solutions. The licensing and overhead costs of the solutions that they are able to retire are $10.0 million in Year 1, $11.5 million in Year 2, and $13.0 million in Year 3.
Forrester assumes that some solutions are left in place and are retired as adoption of Google Cloud’s solutions ramps up.
Risks. An organization’s realization of benefits related to legacy environment savings will depend upon a variety of factors, including:
The types, scale, and costs of existing solutions.
The implementation and scaling of Google Cloud Customer Engagement Suite with Google AI solutions and how well and quickly it is able to replace legacy solutions.
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 $25.5 million.
| Ref. | Metric | Source | Year 1 | Year 2 | Year 3 | |
|---|---|---|---|---|---|---|
| D1 | Legacy solution costs | Interviews | $10,000,000 | $11,500,000 | $13,000,000 | |
| Dt | Legacy environment savings | D1 | $10,000,000 | $11,500,000 | $13,000,000 | |
| Risk adjustment | ↓10% | |||||
| Dtr | Legacy environment savings (risk-adjusted) | $9,000,000 | $10,350,000 | $11,700,000 | ||
| Three-year total: $31,050,000 | Three-year present value: $25,525,920 | |||||
Interviewees and survey respondents mentioned the following additional benefits that their organizations experienced but were not able to quantify:
Improved decision-making. Interviewees shared that Google Cloud’s intent detection, Conversational Agents, and Insights solutions allowed them to better understand what customers in aggregate were calling about and what their drivers were so that they could improve policies and customer-facing information. For instance, the director of AI operations for a travel organization said their organization was actively working to improve its website content to better address common queries, improving the customer experience and reducing how often they needed to contact support.
Improved scalability and organizational agility. A major investment objective for interviewees was to find contact center technologies that improved scalability and flexibility for their organizations. A senior director of engineering for a cybersecurity organization discussed adopting Google Cloud’s CCaaS solution along with Google AI: “With the SaaS model, we have the ability to try out new features without all the upfront investments and commitments. If we say we want Agent Assist, Google can spin it up for us really quickly, we can try it with our agents, and if they like it we’ll continue paying for it. If we don’t, we’ll stop.”
The value of flexibility is unique to each customer. There are multiple scenarios in which a customer might implement Google Cloud Customer Engagement Suite with Google AI and later realize additional uses and business opportunities, including:
Better support for additional languages. A senior director of engineering for a cybersecurity organization explained that by leveraging the machine translation capabilities included with Google Cloud Customer Engagement Suite with Google AI, they were able to reduce the costs of supporting multiple languages without impacting customer satisfaction. A director of AI operations at a travel organization shared that they have been able to add additional languages to their support options with Google Cloud, in part by leveraging AI language models for transcreation.
Reduced agent training time and managerial overhead. Interviewees anticipated that over time, agents would save training and ramp-up time as some activities, such as creating call summaries, were removed from their standard work and as Agent Assist provided support during customer contacts. In addition, call recording and analysis could monitor all calls rather than a sample and provide better insights into coaching opportunities, saving managers time and improving agent performance. A director of AI data and analytics at a telco organization estimated saving 5.5 hours per week per manager for this type of work.
Additional benefits from adopting Google Cloud Customer Engagement Suite with Google AI as an integrated platform. While most interviewees’ organizations currently used a third-party contact center solution, the cybersecurity organization had adopted Google Cloud’s CCaaS platform in addition to its contact center AI solutions. The senior director of engineering for the cybersecurity organization explained: “Having the CCaaS solution brings it all together for you. It’s built on top of Google Cloud technologies, so you have the Conversational Agents integration, integration to all the [channels]. … You have other AI capabilities. When they’re all integrated, it delivers a full contact center solution.”
Future benefits with generative AI. Interviewees shared that they were beginning to test new generative AI features with Conversational Agents, starting with internal use cases. They anticipated additional operational efficiencies and better ability to support agents and customers by leveraging this new technology.
Flexibility would also be quantified when evaluated as part of a specific project (described in more detail in Total Economic Impact Approach).
| Ref. | Cost | Initial | Year 1 | Year 2 | Year 3 | Total | Present Value |
|---|---|---|---|---|---|---|---|
| Etr | Fees paid to Google Cloud | $0 | $5,500,000 | $6,325,000 | $7,150,000 | $18,975,000 | $15,599,174 |
| Ftr | Implementation, ongoing management, and training | $646,800 | $857,340 | $857,340 | $857,340 | $3,218,820 | $2,778,878 |
| Total costs (risk-adjusted) | $646,800 | $6,357,340 | $7,182,340 | $8,007,340 | $22,193,820 | $18,378,052 |
Evidence and data. Interviewees paid Google Cloud based on the solutions deployed, channels, contact volumes and lengths, and professional support needs.
Pricing may vary. Contact Google Cloud for additional details.
Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:
The composite organization has 6,000 agents and fields 24 million contacts per year between voice and chat with an average handle time of 900 seconds.
The composite organization deploys Conversational Agents for voice and chat as well as Agent Assist for call summarization and uses some professional services from Google Cloud.
The composite organization’s use of these solutions increases over time.
Risks. An organization’s costs related to Google Cloud Customer Engagement Suite with Google AI will depend upon a variety of factors, including:
The solutions deployed.
Contact volumes and lengths.
Use cases, scaling, and adoption of the solutions.
Professional support needs.
Changes to Google Cloud’s pricing over time.
Results. To account for these risks, Forrester adjusted this cost upward by 5%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $15.6 million.
| Ref. | Metric | Source | Initial | Year 1 | Year 2 | Year 3 |
|---|---|---|---|---|---|---|
| E1 | Fees paid to Google Cloud | Composite | $5,000,000 | $5,750,000 | $6,500,000 | |
| Et | Fees paid to Google Cloud | E1 | $0 | $5,000,000 | $5,750,000 | $6,500,000 |
| Risk adjustment | ↑10% | |||||
| Etr | Fees paid to Google Cloud (risk-adjusted) | $0 | $5,500,000 | $6,325,000 | $7,150,000 | |
| Three-year total: $18,975,000 | Three-year present value: $15,599,174 | |||||
Evidence and data. Interviewees took different approaches to implementation depending on their starting environment. One interviewee without any IVA in place before Google Cloud started with one open-ended prompt and expanded from there. The other interviewees typically began by replicating existing use cases, integrating systems, and expanding over time. Training for agents was generally minimal.
Interviewees shared that they were able to stand up some initial use cases for Conversational Agents within a few months.
Interviewees said that it took six to eight months to be fully implemented and integrated with key systems at their organizations.
Interviewees shared that ongoing management required a dedicated team of data scientists, data engineers, conversation designers, and technical resources to support the system and continue developing and evolving use cases. The maintenance itself typically only took a couple of hours a week, with the majority of time dedicated to creating new services and flows.
Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:
Initial implementation for Conversational Agents and Agent Assist takes six months. This includes integration with key systems and use case development.
Six individuals are fully dedicated to supporting the implementation. Roles include data scientists, engineers, conversation designers, and software developers.
These six individuals spend 75% of their time in future years supporting the system as well as the continued development of use cases and changes to support evolving business needs.
Training hours for agents are specifically for understanding and working with Conversational Agents and Agent Assist functionality. The initial training dedicated to these solutions during onboarding is 2 hours, with an additional 30 minutes per year of training to understand updated functionality.
Risks. An organization’s costs related to implementing and managing Google Cloud Customer Engagement Suite with Google AI will depend upon a variety of factors, including:
The channels and use cases for which Google Cloud Customer Engagement Suite with Google AI solutions is deployed.
The nature of user contacts, including the complexity and repeatability of contact topics.
The time and effort an organization wants to dedicate to maintaining, tuning, and expanding use cases for Google Cloud Customer Engagement Suite with Google AI solutions.
The roles this organization requires to support the work and the associated cost of labor for those roles.
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 $2.8 million.
| Ref. | Metric | Source | Initial | Year 1 | Year 2 | Year 3 |
|---|---|---|---|---|---|---|
| F1 | Implementation time (months) | Interviews and survey | 6 | |||
| F2 | Resources dedicated to implementation | Composite | 6 | |||
| F3 | Resources dedicated to ongoing management | Composite | 6 | 6 | 6 | |
| F4 | Percentage of time dedicated to ongoing management | Interviews and survey | 75% | 75% | 75% | |
| F5 | Average fully burdened annual salary for resources (blended) | Research data | $160,000 | $160,000 | $160,000 | $160,000 |
| F6 | Subtotal: Implementation and ongoing management | (F1*F2*F5/12)+(F3*F4*F5) | $480,000 | $720,000 | $720,000 | $720,000 |
| F7 | Contact center agents requiring net new training | Composite | 6,000 | 1,800 | 1,800 | 1,800 |
| F8 | Onboarding training time (hours) | Interviews | 2.0 | 2.0 | 2.0 | 2.0 |
| F9 | Contact center agents requiring ongoing training | Composite | 6,000 | 6,000 | 6,000 | 6,000 |
| F10 | Ongoing training time (hours) | Interviews | 0.0 | 0.5 | 0.5 | 0.5 |
| F11 | Average fully burdened hourly agent rate | Composite | $9.00 | $9.00 | $9.00 | $9.00 |
| F12 | Subtotal: Training | (F7*F8*F11)+(F9*F10*F11) | $108,000 | $59,400 | $59,400 | $59,400 |
| Ft | Implementation, ongoing management, and training | $588,000 | $779,400 | $779,400 | $779,400 | |
| Risk adjustment | ↑10% | |||||
| Ftr | Implementation, ongoing management, and training (risk-adjusted) | $646,800 | $857,340 | $857,340 | $857,340 | |
| Three-year total: $3,218,820 | Three-year present value: $2,778,878 | |||||
| Initial | Year 1 | Year 2 | Year 3 | Total | Present Value | |
|---|---|---|---|---|---|---|
| Total costs | ($646,800) | ($6,357,340) | ($7,182,340) | ($8,007,340) | ($22,193,820) | ($18,378,052) |
| Total benefits | $0 | $17,908,000 | $23,685,003 | $27,329,000 | $68,922,003 | $56,387,064 |
| Net benefits | ($646,800) | $11,550,660 | $16,502,663 | $19,321,660 | $46,728,183 | $38,009,012 |
| ROI | 207% |
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.
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.
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.
From the information provided in the interviews and survey, Forrester constructed a Total Economic Impact™ framework for those organizations considering an investment in Google Cloud Customer Engagement Suite with Google AI.
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 Google Cloud Customer Engagement Suite with Google AI can have on an organization.
Interviewed Google Cloud stakeholders and Forrester analysts to gather data relative to Google Cloud Customer Engagement Suite with Google AI.
Interviewed four decision-makers and surveyed 160 respondents at organizations using Google Cloud Customer Engagement Suite with Google AI to obtain data about costs, benefits, and risks.
Designed a composite organization based on characteristics of the interviewees’ and survey respondents’ organizations.
Constructed a financial model representative of the interviews and survey using the TEI methodology and risk-adjusted the financial model based on issues and concerns of the interviewees and survey respondents.
Employed four fundamental elements of TEI in modeling 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.
Benefits represent the value the solution delivers to the business. The TEI methodology places equal weight on the measure of benefits and costs, allowing for a full examination of the solution’s effect on the entire organization.
Costs comprise all expenses necessary to deliver the proposed value, or benefits, of the solution. The methodology captures implementation and 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. 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.
Total Economic Impact is a methodology developed by Forrester Research that enhances a company’s technology decision-making processes and assists solution providers in communicating their value proposition to clients. The TEI methodology helps companies demonstrate, justify, and realize the tangible value of business and technology initiatives to both senior management and other key stakeholders.
| In which country are you located? | |
|---|---|
| United States | 26% |
| United Kingdom | 13% |
| India | 12% |
| Singapore | 11% |
| Japan | 10% |
| Germany | 9% |
| Canada | 8% |
| The Netherlands | 7% |
| Belgium | 5% |
| Using your best estimate, what is your organization’s annual revenue? | |
|---|---|
| $300M to $399M | 11% |
| $400M to $499M | 25% |
| $500M to $999M | 26% |
| $1B to $5B | 23% |
| >$5B | 15% |
| How many contact center agents are in your organization? | |
|---|---|
| <100 | 0% |
| 100-500 | 9% |
| 501-1,000 | 21% |
| 1,001-2000 | 18% |
| 2,001-3,000 | 18% |
| 3,001-4,000 | 14% |
| 4,001-5,000 | 12% |
| 5,001-10,000 | 5% |
| More than 10,000 | 4% |
| Which of the Google Cloud AI services are you using in your contact center? | |
|---|---|
| Agent Assist | 85% |
| Conversational Agents/Dialogflow | 81% |
| Conversational Insights | 72% |
Note: Percentages may not total 100 because of rounding.
Related Forrester Research
The Conversation Intelligence Solutions For Contact Centers Landscape, Q1 2025, Forrester Research, Inc., January 24, 2025.
The Contact-Center-As-A-Service Platforms Landscape, Q4 2024, Forrester Research, Inc., October 24, 2024.
Lessons Learned From The Forrester Wave™: Conversational AI For Customer Service, Q2 2024, Forrester Research, Inc., October 7, 2024.
Generative AI Is The Catalyst For Change In The Contact Center, Forrester Research, Inc., June 20, 2024.
Generative AI Promises Conversational CX for Customers And CX Pros, Forrester Research, Inc., December 8, 2023.
Generative AI Essentials For CX Leaders, Forrester Research, Inc., September 26, 2023.
The Promise Of Generative AI For CX, Forrester Research, Inc., July 11, 2023.
Generative AI: What It Means For Customer Service, Forrester Research, Inc., July 7, 2023.
1 Source: The Forrester Tech Tide: Contact Centers For Customer Service, Q4 2024, Forrester Research, Inc., October 30, 2024; The Conversational AI For Customer Service Landscape, Q4 2023, Forrester Research, Inc., November 15, 2023; The State Of Conversational AI, Forrester Research, Inc., September 6, 2024.
2 Total Economic Impact is a methodology developed by Forrester Research that enhances a company’s technology decision-making processes and assists solution providers in communicating their value proposition to clients. The TEI methodology helps companies demonstrate, justify, and realize the tangible value of business and technology initiatives to both senior management and other key stakeholders.
3 Source: Money On The Table: Proof That Customer Service Drives Revenue, Forrester Research, Inc., January 30, 2023.
Readers should be aware of the following:
This study is commissioned by Google Cloud 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 study to determine the appropriateness of an investment in Google Cloud Customer Engagement Suite with Google AI. For any interactive functionality, the intent is for the questions to solicit inputs specific to a prospect’s business. Forrester believes that this analysis is representative of what companies may achieve with Google Cloud Customer Engagement Suite with Google AI based on the inputs provided and any assumptions made. Forrester does not endorse Google Cloud or its offerings. Although great care has been taken to ensure the accuracy and completeness of this model, Google Cloud and Forrester Research are unable to accept any legal responsibility for any actions taken on the basis of the information contained herein.
Google Cloud 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.
Google Cloud provided the customer names for the interviews but did not participate in the interviews.
Forrester fielded the double-blind survey using a third-party survey partner.
Elizabeth Preston
May 2025
ABOUT FORRESTER CONSULTING
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© Forrester Research, Inc. All rights reserved. Unauthorized reproduction is strictly prohibited. Information is based on best available resources. Opinions reflect judgment at the time and are subject to change. Forrester®, Technographics®, Forrester Wave, and Total Economic Impact are trademarks of Forrester Research, Inc. All other trademarks are the property of their respective companies.
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