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Executive Summary

As consumers blur the lines between different channels, the challenge of linking marketing spending to business results intensifies. Marketers need to be accountable for their spending, but this is easier said than done - harmonizing data from multiple channels that were never designed to work together is complex and time-consuming. Marketers need solutions that provide “right-time”, unified insights across omnichannel marketing initiatives to guide their next moves and investments.


Adverity provides a data and analytics platform to help organizations improve and speed up the way they make insights-driven marketing decisions.

Adverity 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 Adverity end-to-end data and analytics platform. The purpose of this study is to provide readers with a framework to evaluate the potential financial impact of Adverity’s platform on their organizations.

To better understand the benefits, costs, and risks associated with this investment, Forrester interviewed the decision-maker of an organization that has experience using the Adverity platform. Forrester used this experience to project a three-year financial analysis.

Prior to using Adverity’s data and analytics platform, the interviewee noted that their organization was “doing marketing in the dark.” Although the global marketing performance team did run analytics and reporting on its marketing activities, this was usually siloed by channel, giving the organization a limited oversight of its overall performance. Furthermore, a lot of the analytics work was fragmented. As a result, the organization was often not able to make marketing decisions backed by data and insights in a timely manner.

The Adverity platform’s data connectivity and dashboard reporting helped speed up the time-to-insight for the organization, and provided a near real-time, omnichannel view of its marketing performance. The decision-maker and their organization now had data and insights at their fingertips and could use it to make timely decisions on ongoing marketing activities.

Key Findings

Quantified benefits

Risk-adjusted present value (PV) quantified benefits include:

  • Timely insights on performance, allowing for optimization of marketing activities. The Adverity platform allowed the organization to monitor its marketing campaigns in near realtime, giving it the opportunity to adapt its tactics (e.g., channel priorities and ad spend) quickly. For instance, it could pause or boost advertising spend as needed or reallocate the ad spend across different channels. Overall, the flexibility to optimize campaigns allowed the organization to save and reallocate an estimated $2.9 million in what would have been wasted ad spend over three years.
  • Improved efficiency in data management and operations. With Adverity, the organization was able to automate many of the manual and time-consuming processes around its data operations. In particular, the interviewee highlighted that the global marketing insights and performance team, which comprised of six staff, was able to “free up 80% of [its] time,” which was mostly spent on manual data processes (e.g., data integration, data mapping, schema mapping, data cleansing, data unification, etc.). These time and resource savings add up to about $564,000 over three years and, more importantly, free up employees’ time to focus on actual data analysis.
  • Time savings from marketing analytics activities. The interviewee estimated that local marketing teams could cut down about 75% of their time spent on these activities. Having access to automatically updated reports and dashboards through Adverity saved local marketing teams significant time and effort on running weekly or monthly spreadsheet-based reports. With teams spread over 70+ markets worldwide, this amounted to significant time savings of about $1.8 million over three years.



Unquantified benefits

The customer organization also experienced some additional benefits which were not quantified in the financial model:

  • Migration towards becoming a data-driven organization. The interviewed decision-maker highlighted that Adverity’s platform was a trigger for their organization to accelerate the cultural shift towards becoming a data-driven organization.
  • Improved collaboration through data democratization. Furthermore, having marketing data and insights now accessible for all employees across the organization paved the way for more collaboration across teams.
  • Improved job satisfaction and employee experience. Employees working on marketing data no longer have to deal with cumbersome tools and processes to prepare data for analysis and can instead focus on more rewarding and valuable aspects of their jobs.


Risk-adjusted PV costs include:

  • Adverity subscription and professional service fees, amounting to $998,000 over three years.
  • Internal project management costs, including fees paid to an external project manager, as well as ongoing effort spent on managing the solution. These project management costs added up to about $133,000 over three years.

Overall, the interview and financial analysis found that the decision-maker’s organization experienced benefits of $5.29 million over three years versus costs of $1.13 million, adding up to a net present value (NPV) of $4.16 million and an ROI of 368%.


TEI Framework and Methodology

From the information provided in the interviews, Forrester constructed a Total Economic Impact™ framework for those organizations considering an investment in the Adverity data and analytics 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 the Adverity platform can have on an organization.

Due Diligence
Interviewed Adverity stakeholders and Forrester analysts to gather data relative to the Adverity data and analytics platform.

Decision-Maker Interview
Interviewed the decision-maker of an organization using the Adverity platform to obtain data with respect to costs, benefits, and risks.

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 decision-maker.

Case Study
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.

Readers should be aware of the following:
This study is commissioned by Adverity 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 the Adverity platform. Adverity 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. Adverity provided the customer name for the interview but did not participate in the interview.

The Adverity Customer Journey

Interviewee's Organization 

To build the financial model used in this study, Forrester interviewed the decision-maker of an organization that had been using the Adverity data and analytics platform for the past year. This organization is a global manufacturer of consumer electricals across dozens of brands. It generates over $7 billion in revenue yearly and employs over 35,000 employees in over 70 countries.

Company overview

Consumer electricals
US $7 billion in annual revenue
Over 35,000 employees
More than 70 markets

Key Challenges

Prior to investing in Adverity’s platform, the interviewee’s organization had limited and isolated views of how its marketing campaigns were performing. The views were restricted to channel-centric reports and the organization could not get a full oversight of what was happening across channels. The interviewee noted how their organization struggled with common challenges, including:

Lack of omnichannel view of marketing performance, leading to difficulties in proving marketing’s value. The organization was limited to analyzing its marketing performance in siloes. While there were attempts to merge data from different sources, it was not able to do so in real time as it was still using manual, spreadsheet-based processes for data analytics. The interviewed decision-maker described the process of analyzing data from different sources as laborious. Their organization faced challenges with combining data insights from all digital channels and prioritizing business decisions on the findings. Furthermore, this also made it difficult for the marketing organization to prove its value.

Slow time-to-insights that limited its ability to optimize marketing campaigns as they were running. With all the work the marketing teams had to do to get reports ready, they were simply unable to assess and adjust marketing campaigns quickly.

Wasted time on inefficient reporting and analytics. Having to work with such disparate tools meant that employees had to regularly spend a significant amount of time on low-value tasks like cleaning and merging data, running reports, etc.

“We were doing marketing in the dark. We had spreadsheet-based reporting, which is like looking in the rear mirror at what happened last month, but we were not able to look forward and steer.”

Head of Marketing Insights and Performance

Use Case Description

After a request for proposal (RFP) and business case process evaluating multiple vendors, the decision-maker’s organization decided on Adverity based on its out-of-box capabilities, deployment simplicity, as well as the cultural fit between the two organizations.

The organization started with connecting data from key marketing channels (including Adobe Analytics, Google Ads, Facebook, LinkedIn, YouTube) as well as some internal databases. It also established some cross-channel dashboards and metrics such as return on ad spend to track.

As a large organization with hundreds of marketing teams around the globe, it took a phased approach to deployment. It used Adverity’s platform to first track and manage global marketing campaigns that were run centrally, testing the platform before bringing local marketing teams on board.

This phased approach was part of its change management plan and allowed the organization to prove the effectiveness of Adverity before a full deployment. Its efforts around change management have also been factored into the financial model in this study.

For this case study, Forrester based the financial model on the data shared by the interviewee. The figures presented in Years 2 and 3 are projections based on the interviewee’s feedback and experience with deploying Adverity in their first year of use.

“Normally you would have to build an API or Python script to integrate data from different sources, but with Adverity, you just specify the access details for the specific data feed and it’s done.”

Head of Marketing Insights and Performance

Analysis Of Benefits


Marketing Spend Optimization

Evidence and data. The interviewed decision-maker highlighted that the Adverity platform’s information allowed for significant savings with near real-time spend optimization for all digital marketing campaigns. They reported that one of the organization’s biggest challenges was not being able to adjust its campaigns in near real time, and that it lacked full insights on each dollar spent on its marketing and advertising efforts. Adverity’s platform provided new insights on the effectiveness of its marketing programs.

In the past, individual campaign activities were monitored on weekly or monthly basis, so teams could not make timely decisions to optimize the campaigns as they only had insufficient and isolated insights. With Adverity, the team is now able to assess results across all channels within a couple of days and adapt as it sees fit. For instance, it could now pause or boost advertising spend or reallocate its money across different channels as needed, instead of waiting weeks to review their performance. If the team had to wait, the campaign would have incurred more in additional ad spend.

Modeling and assumptions. For the financial model, Forrester assumes:

  • The organization operates in 70 markets, has seven brands, and runs six marketing campaigns per brand, per market annually.
  • Out of eight global marketing campaigns run in Year 1, the organization was able to optimize one of them using the Adverity platform. It expects to increase the number of campaigns optimized to five by Year 3.
  • As it becomes a more mature, data-led organization, and as it onboards more local marketing teams onto the Adverity platform, it expects to increase the number of optimized local marketing campaigns from 0% in Year 1 to 15% in Year 3.

Risks. Factors that could impact the realization of this benefit include:

  • Inertia to change. Local marketing teams and decision-makers may be used to old ways of working and looking at campaign performances weekly or monthly, and they might not always be in favor of optimizing campaigns in real time.
  • Organizational culture. Data-driven decision-making requires a cultural change within an organization. The speed at which organizations adapt to this new way of working will also have an impact on their ability to make fast decisions.

Results. To account for these risk factors, Forrester adjusted this benefit downward by 15%, yielding a three-year, risk-adjusted total present value (discounted at 15%) of almost $2,934,00.


“For the first time ever, we have the ability to calculate our return on investment or ad spend.”

Head of Marketing Insights and Performance

Improved Efficiency in Data Management and Operations

Evidence and data. One of the key benefits the interviewed decision-maker highlighted was the time savings the global marketing insights team experienced with data analytics operations. Previously, the team of six data analysts had to manually clean, merge, and map data from multiple sources before it could be analyzed. The team then had to spend additional time preparing charts and reports, disseminating these reports across the organization, etc. This process was repeated weekly or monthly, time-consuming, and simply not sustainable.

The interviewed decision-maker reported that with Adverity many of the reports and dashboards could be run and updated automatically. This freed up about 80% of the data analysts’ time that they previously spent on these manual tasks.

Modeling and assumptions. For this financial model, Forrester assumes that, of the total time savings, 75% of it is captured and put back into more value-add work like analyzing data.

Risks. Several factors that could impact the realization of this benefit include:

  • How mature an organization’s data operations were prior to the investment.
  • The culture within the organization, specifically how open to change it is.

Results. To account for these risks, Forrester adjusted this benefit downward by 10%, yielding a three-year, risk-adjusted total present value of over $564,000.



“Time savings was the key benefit for our team — we freed up 80% of our time that we were spending on data integration, mapping, and cleansing.”

Head of Marketing Insights and Performance

Time Savings On Marketing Analytics Activities

Evidence and data. The local marketing teams spread throughout the more than 70 markets the organization is in also benefitted from the Adverity deployment. Adverity helped to streamline their marketing analytics activities. For instance, where they previously had to spend time consolidating and merging data from different marketing channels to analyze their campaign performance, they could now easily access this data on Adverity. The interviewee estimates that local marketing managers and analysts could reduce the time they were spending on marketing analytics activities by 75%.

Modeling and assumptions. For this financial model, Forrester makes the following assumptions:

  • A general marketer (i.e., one that oversees multiple aspects of marketing) spends about 6 hours per week (or about 15% of their time) on marketing analytics activities. This includes logging onto different channels and platforms, downloading individual reports, and reconciling them into a single overview report.
  • Employees take a while to adopt to new ways of working and switch from their old ways, and it takes two to three years for all marketing employees to get on board with using Adverity’s platform for their marketing analytics.
  • Of the time saved, 75% is captured and put back into more value-add work.

Risks. Several factors that could impact the realization of this benefit include:

  • How mature an organization’s data operations were prior to the investment.
  • The culture within the organization, specifically how open to change it is.
  • The effectiveness of change management efforts to introduce a dispersed marketing workforce to a new way of working.

Results. To account for these risks, Forrester adjusted this benefit downward by 10%, yielding a three-year, risk-adjusted total present value of over $1,793,000.




Unquantified Benefits

The customer also experienced some additional benefits which have not been quantified and included in the financial model:

Transformation into a data-driven organization. The interviewed decision-maker highlighted that Adverity triggered an acceleration towards the organization becoming more data-driven.

“We used Adverity to support the liberalization of data in our organization. … Even at the C-level, some executives are now using Adverity daily. I never would have imagined this would be possible — so the platform itself is autonomously driving a cultural change.”

Head of Marketing Insights and Performance

Improved collaboration through data democratization. Having marketing data and insights now accessible for all employees across the organization also paved the way for more collaboration across teams. In particular, the decision-maker mentioned that sales teams were now proactive in looking into these marketing insights.

Improved job satisfaction and employee experience. Employees working on marketing data no longer have to deal with cumbersome tools and processes to prepare data for analysis and can instead focus on more rewarding and value-add aspects of their jobs.

“Instead of looking at their own silo, we now urge everyone in marketing, and partly in sales, to look at the performance end-to-end so they can see the impact of their investments.”

Head of Marketing Insights and Performance


The value of flexibility is unique to each customer. There are multiple scenarios in which a customer might implement and later realize additional uses and business opportunities, including:

Opportunities for marketing automation. By integrating Adverity with other platforms or channels, organizations could potentially set rules and guidelines that would optimize campaign parameters in real time according to actual performance.

Predictive analytics. Another potential use case is predictive analytics based on Adverity’s AI-powered analytics engine. While this is a capability already offered by Adverity, the organization had not started testing this use case.

Flexibility would also be quantified when evaluated as part of a specific project (described in more detail in Appendix A).

Analysis Of Costs


Total Adverity Fees

Evidence and data. The primary costs associated with Adverity are the subscription fees. The subscription fees presented in this financial model were provided by the interviewed decision-maker and will vary by organization and use case. The interviewed decision-maker also engaged Adverity to help with integrating their data sources onto the platform, incurring some professional service costs at the start of the project.

Risks. These fees are largely dependent on the scale of deployment and vary based on the number of data sources connected to the platform and the volume of data to be analyzed.

Results. To account for these variances, Forrester adjusted this cost upward by 10%, yielding a three-year, risk-adjusted total present value (discounted at 10%) of over $998,000.




Associated Project Management Costs

Evidence and data. The second category of costs the decision-maker’s organization incurred with the Adverity investment is project management costs.

To help with implementation, the organization engaged an external project manager for six months, incurring $114,000 at the start of the project.

Once fully deployed, there is minimal effort to manage the administrative aspects of Adverity on an ongoing basis.

Results.To account for variances in complexity of deployment, Forrester adjusted this cost upward by 10%, yielding a three-year, risk-adjusted total present value of almost $133,000.


Financial Summary

Consolidated Three-Year Risk-Adjusted Metrics

The financial results calculated in the Benefits and Costs sections can be used to determine the ROI, NPV, and payback period for the 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.


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 realize the tangible value of IT initiatives to both senior management and other key business stakeholders.


Total Economic Impact Approach

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 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.

Present Value (PV)
The present or current value of cost and benefit estimates, assuming an interest rate (or discount rate) of 10%. The PV of costs and benefits feed into the total NPV of cash flows.

Net Present Value (NPV)
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.

Return On Investment (ROI)
A project’s expected return in percentage terms. ROI is calculated by dividing net benefits (benefits less costs) by costs.

Discount Rate
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%.

Payback Period
The breakeven point for an investment. This is the point in time at which net benefits (benefits minus costs) equal initial investment or cost.

Appendix B: Supplemental Material

Related Forrester Research

“Marketing Measurement Morphs Into Insight-Driven Marketing,” Forrester Research, Inc., October 4, 2021.

“Chart Your Course To Marketing Measurement Maturity,” Forrester Research, Inc., December 1, 2020.

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Adverity commissioned Forrester Consulting to conduct a Total Economic Impact (TEI) study and examine the potential return on investment (ROI) companies may realize by deploying our end-to-end data and analytics platform.