For: Customer Insights Professionals Gauging Web Analytics Practices In The Age Of The Customer by James McCormick, June 10, 2014 Key Takeaways Web Analytics Alone Is Insufficient To Deliver Digital Intelligence Emerging channels, sophisticated consumers, technical challenges, and the democratization of analytics within data-driven enterprises cannot be tackled using traditional web analytics approaches. Digital intelligence requires a commitment to multiple technologies and approaches to support broad data, analysis, and action requirements. Web Analytics Is Critical To Businesses This benchmark study shows that web analytics practices are a core competency within marketing and ecommerce teams. As CI professionals prefer to manage the tools themselves rather than outsource work to external partners, they select their web analytics vendor based on the tool s ability to directly service their business needs. Firms Don t Like Changing Their Web Analytics Vendor For reasons both good and bad, CI professionals have deeply established relationships with their web analytics vendors. Although vendors have done well to advance their technology and services in line with users advancing needs, some users feel stuck with their vendors, as changing would be too disruptive and costly to their business. Forrester Research, Inc., 60 Acorn Park Drive, Cambridge, MA 02140 USA Tel: +1 617.613.6000 Fax: +1 617.613.5000 www.forrester.com
June 10, 2014 Gauging Web Analytics Practices In The Age Of The Customer Benchmarks: The Digital Intelligence Playbook by James McCormick with Mary Pilecki and Samantha Ngo Why Read This Report In the Q2 2014 Forrester Wave evaluation of web analytics platforms, we surveyed 54 web analytics customers about their web analytics practices. It s clear from this benchmark data that web analytics remains central to marketers digital intelligence requirements by supporting multichannel analytics, democratizing insights across multiple stakeholders and businesses, and applying them at the speed of the customer. This study finds a mature web analytics industry where key differentiators are no longer features and functionality, but services and satisfaction. Longstanding vendor relationships exist out of hardearned loyalty as well as reluctance to change because of effort and costs. Now is the time for customer insights (CI) professionals to evaluate their existing vendor relationships and make web analytics part of their digital intelligence road map. Table Of Contents 2 10 13 13 Web Analytics Supports Digital Intelligence Requirements Web Analytics Is Firmly Embedded In The Business Multiple Tools Deliver Digital Intelligence Web Analytics Has A Role In Cross-Channel Optimization CI Professionals Are Loyal To Their Web Analytics Vendors recommendations Make Web Analytics Part Of Your Digital Intelligence Road Map Supplemental Material Notes & Resources As part of the Q2 2014 Forrester Wave evaluation of web analytics vendors, Forrester conducted product evaluations in February 2014 and interviewed six vendor companies: Adobe, AT Internet, Google, IBM, SAS Institute, and Webtrends. Forrester also interviewed 14 end user companies and surveyed 54 customers of these web analytics vendors. Related Research Documents The Forrester Wave : Web Analytics, Q2 2014 May 13, 2014 Decipher The Digital Intelligence Technology Code April 3, 2014 Digital Intelligence Replaces Web Analytics November 11, 2013 2014, 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, RoleView, TechRadar, and Total Economic Impact are trademarks of Forrester Research, Inc. All other trademarks are the property of their respective companies. To purchase reprints of this document, please email clientsupport@forrester.com. For additional information, go to www.forrester.com.
Gauging Web Analytics Practices In The Age Of The Customer 2 Web Analytics Supports Digital Intelligence Requirements To meet the analytics challenges presented by the current breadth of channels and devices and by the speed of digital interactions, the practice of web analytics has been subsumed into what Forrester has defined as digital intelligence. 1 Digital intelligence brings a set of expanded requirements on technology frameworks, organizational structures, metrics, and optimization practices that extend beyond the remit of web analytics tools. However, web analytics is still core to digital intelligence practices and must at least support, if not deliver on, these advanced requirements. Web Analytics Is Firmly Embedded In The Business Leading online gaming firms demonstrate the best practice of giving analytics exposure in the business far beyond network operations and siloed teams of statisticians. 2 Web analytics respondents strongly indicate that this change in ownership model is not isolated. In fact, as a central function within digital intelligence practices, ownership of web analytics has changed: Business ownership of web analytics has increased. CI pros have pushed vendors to support business requirements, and with advances in application ease of use, businesses have wrested ownership of web analytics from technical teams. Today over two-thirds of web analytics practices are owned by marketing or ecommerce, up from 55% in 2011 (see Figure 1). 3 Web analytics has become a core competency. In the age of the customer, competitive firms place the customer at the center of their operations. 4 Delivering customer centricity at scale demands that customer data capabilities are core competencies. Digital data is no exception: 62% of web analytics practices are managed in-house, and they are largely independent of services offered by external agencies, consultancies, or professional services (see Figure 2). Web analytics supports business needs. The most important consideration when selecting web analytics vendors is the ability to service business needs, via a mix of application and vendor services (see Figure 3). While flexibility of the application to meet business needs is important, CI pros must not forget to evaluate vendors on their ability to support the web analytics practice with services. One director of digital marketing for a global online retailor informed Forrester that the quality of the support and service were a differentiating factor and a key advantage for their firm s chosen web analytics vendor.
Gauging Web Analytics Practices In The Age Of The Customer 3 Figure 1 Over Two-Thirds Of Web Analytics Practices Are Owned By Marketing Or ecommerce What department in your firm is responsible for web analytics? Marketing 43% ecommerce 25% Business intelligence or corporate analytics group Other, please specify 9% 19% 68% IT 4% Finance 0% Base: 54 vendor client references Figure 2 Customer Insights Professionals Prefer To Manage Web Analytics Themselves What is your firm s method of measuring web analytics? * 62% in-house 15% work with web analytics vendor s professional service group 6% work with an external agency or consultancy Base: 54 vendor client references *Note: 17% answered Other ; 0%, Allow external agency or consultancy to manage entire process.
Gauging Web Analytics Practices In The Age Of The Customer 4 Figure 3 Web Analytics Tools Must Support Business Users Which of the following are the three most important factors when selecting a web analytics vendor or application? Ability to service my business needs Flexibility of reporting options Accuracy of information 43% 42% 47% Total cost of ownership 32% Ease of integration with other data types Training and services supporting offering Ability to connect visitor data with customer data Real-time reporting Thought leadership Standard features and functionality Data collection method User interface Cross-channel attribution Attribution 21% 17% 13% 13% 11% 11% 9% 9% 8% 8% Referencing customers Reputation of company Ability to measure new media Other, please specify 4% 4% 4% 2% Base: 53 vendor client references (up to three responses accepted) Multiple Tools Deliver Digital Intelligence Digital intelligence requires a strong technology commitment to support broad data, analysis, and action requirements. 5 A tedious consequence is that CI pros must master multiple techniques to bring together comprehensive digital intelligence capabilities. Multiple techniques require multiple tools. To support digital intelligence requirements:
Gauging Web Analytics Practices In The Age Of The Customer 5 Firms use multiple web analytics tools. Nine out of 10 firms we surveyed use multiple web analytics tools (see Figure 4). The most common scenario is firms employing an enterprise web analytics platform managed by a corporate marketing or analytics team. Outside of the corporate remit, some parts of the business deploy their own user-friendly web analytics tool, typically Google Analytics free version. Why? Because they don t get corporate support for their specific analytics needs, and the accessibility of some free tools feels like an irresistible workaround to deliver basic needs. Different web analytics tools serve different purposes. Web analytics as a practice has advanced in sophistication and scope within enterprises, and no single tool can deliver all web analytics requirements (see Figure 5). Some firms use separate web analytics tools to service specific, advanced functional needs (e.g., analyzing multiple sources of online and offline data), while others do so simply because each tool matches the skill sets and needs of specific users (e.g., analytics, marketing, business). Digital intelligence needs more than web analytics tools. While the tracking, measuring, and analytics capabilities of web analytics are core to digital intelligence, complete digital intelligence solutions require a range of technical capabilities. Firms are beginning to add digital intelligence capabilities to complement their web analytics tools. Forty-seven percent of firms using web analytics also use voice of the customer (VoC) tools, and 32% of firms use web interaction analysis tools (see Figure 6). 6
Gauging Web Analytics Practices In The Age Of The Customer 6 Figure 4 Nine Out Of 10 Firms Use Multiple Web Analytics Tools Please select any web analytics tools that your firm currently has developed in live production in addition to the vendor that sent you this survey. 66% 15% 13% 11% 9% 6% 4% 2% 17% DIGITAL ANALYTICS Other No additional i vendor Base: 53 vendor client references
Gauging Web Analytics Practices In The Age Of The Customer 7 Figure 5 Multiple Web Analytics Tools Support Digital Intelligence Why does your firm utilize multiple web analytics applications? Different tools have been selected and implemented to serve specific analysis purposes 40% A secondary tool serves as an audit point for the primary application 34% Different user groups are given tools that match their requirements and skill sets Different parts of the company have independently selected and implemented different tools 23% 23% We do not use multiple web applications Multiple tools are used as a costsavings strategy where free or less expensive tools are used on certain sites/domains that do not require advanced analysis or rollup reporting 15% 21% Other, please specify 6% Base: 54 vendor client references (multiple responses accepted)
Gauging Web Analytics Practices In The Age Of The Customer 8 Figure 6 Firms Are Starting To Use Other Digital Analytics Techniques Does your firm use a voice of the customer or web interaction analysis tool in addition to the web analytics vendor we are evaluating? Voice of the customer Web interaction analysis No 53% Yes 47% No 68% Yes 32% Nearly half of surveyed respondents use voice of the customer tools. Base: 53 vendor client references Almost one third of surveyed respondents use web interaction analysis tools. Web Analytics Has A Role In Cross-Channel Optimization Digital intelligence requires support for cross-channel attribution as well as experimentation to accurately assess and compare the impact of content, promotions, and experiences across digital interaction points. While some of these requirements extend beyond the capabilities of today s web analytics tools, their role is one of an enabler, as CI professionals expect these tools to support them with: Optimizing channel investments. Measuring channel performance with web analytics (attribution) is one of the top two challenges respondents seek to resolve (see Figure 7). Basic support from top web analytics tools is provided directly by capabilities within the tools. However, where more advanced cross-channel attribution is needed, web analytics tools should act as a supplier of digital customer data to cross-channel attribution platforms. 7 Enhancing customer experience. Important to digital intelligence is the capability to proactively deliver the most relevant experiences by predicting how customers will respond and then learning from how they actually respond. Sixty percent of respondents think that web analytics should support predictive analytics, and almost 50% think it should support testing (see Figure 8).
Gauging Web Analytics Practices In The Age Of The Customer 9 Figure 7 Web Analytics Tackles Cross-Channel Performance Which topics represent the three greatest challenges that you seek to resolve with your web analytics solutions? Visitor segmentation Marketing attribution Data integration 42% 40% 45% Pathing analysis Content value 26% 30% Customer engagement A/B and multivariate testing Merchandising analysis 21% 19% 19% Measuring mobile applications Measuring mobile browsing Measuring rich media such as application and video Others, please specify Page/task abandonment Measuring social media 13% 11% 8% 6% 6% 4% Base: 53 vendor client references (up to three responses accepted)
Gauging Web Analytics Practices In The Age Of The Customer 10 Figure 8 Prediction And Optimization Are Top 10 Requirements Regardless of whether or not your current vendor offers these features, which of the following attributes are or would be most beneficial to your business? Predictive analytics, based on behavior or some other methodology Ability to compare customer data across client base* 57% 60% Ability to measure campaign attribution Real-time data monitoring for basic traffic metrics Ability to create, update, and share customer profile information across applications Ability to export web analytics data for blended data analysis A/B or multivariate testing functionality Ability to correlate multiple data dimensions 55% 55% 53% 51% 49% 48% Ability to measure clicks leading offsite Ability to manage tags and measurement instrumentation more easily 40% 38% Base: 53 vendor client references (multiple responses accepted) *Note: E.g., compare conversion rates, AOV, revenue per visitor, browser share, traffic from search engines. Note: Real-time data monitoring is defined as visitor clicks in 10 seconds or less. CI Professionals Are Loyal To Their Web Analytics Vendors The practice of web analytics has been honed since the beginning of the century, and some of the vendors in the Q2 2014 web analytics Forrester Wave evaluation have evolved to support its advancing needs. Firms have established long-term relationships with their web analytics vendors; over half of the firms surveyed have been with their vendors for more than four years (see Figure 9). What s more, firms are reluctant to change. Over 60% of respondents claimed they would not consider changing vendors even if, for a lower price, another could provide the exact same capabilities (see Figure 10). As with most long-term relationships, there are both good and bad reasons for sticking together:
Gauging Web Analytics Practices In The Age Of The Customer 11 Why you should stick with your web analytics vendor. Top web analytics vendors are keeping up with advancing needs. While features and functions still differentiate one top vendor from the next, the real differentiation comes with the after-sales services. Vendors with the highest growth in their web analytics business also enjoy high customer satisfaction levels with the services they offer. The director of digital analytics for an online retailer said that although the software is obviously a critical part of the solution, I also feel strongly that it is the quality of the support and service which is the differentiating factor. Why you shouldn t stay with your web analytics vendor. Some firms feel stuck to their web analytics vendor. Their measurement programs are mature, and their web analytics tools are tightly integrated into their existing systems and teams. Firms believe that the cost of unpicking this technology and re-implementing a new technology would be too costly. What they fail to consider are the lost opportunity costs associated with not innovating with new technologies and approaches. Figure 9 Firms Have Longstanding Relationships With Their Web Analytics Vendors How long has your current vendor been your web analytics provider? 5 years or longer 38% 4 to less than 5 years 15% 3 to less than 4 years 9% 2 to less than 3 years 1 to less than 2 years 17% 15% 53% 6 months to less than 1 year 6% Less than 6 months Don t know 0% 0% Base: 54 vendor client references
Gauging Web Analytics Practices In The Age Of The Customer 12 Figure 10 Firms Hate Swapping Web Analytics Vendors Because It s Costly If you could find the exact capabilities elsewhere for a lower price, would you consider switching to a different vendor? Yes, we would consider switching vendors 36% No, we would not considers switching vendors 64% Which of the following reasons would prevent you from switching to another web analytics provider? * The cost of switching is too high We are too tightly integrated with our current provider We are totally satisfied with our current provider We don t believe we could find the same capabilities and value elsewhere We do not want to learn a new application We rely on their support and services We do not want to train another vendor on our business Our firm has a multi-product and/or multiservice contract with our vendor Others, please specify 4% 19% 25% 23% 34% 32% 47% 51% 51% Base: 53 vendor client references Source: Q1 2014 Global Web Analytics Forrester Wave Customer Online Survey *Note: Responses to this question were provided by respondents who said they were not willing to switch vendors.
Gauging Web Analytics Practices In The Age Of The Customer 13 recommendations Make Web Analytics Part Of Your Digital Intelligence Road Map While the digital intelligence remit has advanced beyond what can be delivered by today s web analytics tools, the respondents to the Forrester Wave user survey have made it clear that web analytics tools have a vital role to play within digital intelligence programs. As they make web analytics part of their digital intelligence road map, CI professionals should: Rationalize the number of web analytics tools. While in some instances multiple tools are unavoidable, multiple web analytics tools create barriers to cross-business understanding and engagement of customers. Corporate analytics teams should routinely audit the use of free tools such as Google Analytics (free version) across different businesses and regions. Using this input, firms should build the business case to support growing demand using the enterprise web analytics tool of choice. Reduce web analytics vendor stickiness. Long-term relationships reduce disruption to the business and help vendors better support the business; however, entrenched web analytics vendors can inhibit innovation and create vendor complacency. To keep their technology partners on their toes, CI professionals must adopt techniques and strategies, such as tag management processes, which enable firms to evaluate new technologies and swap out legacy systems with minimal fuss. Release insights from web analytics tools. Top web analytic vendors have built advanced capabilities such as customer profiling, predictive analytics, and real-time data availability. To support other systems and tools in the digital intelligence ecosystem, CI professionals must make these capabilities and insights available to other systems (e.g., online testing and remarketing tools) in real-time to inform and optimize customer engagements creating a technology ecosystem that delivers true digital intelligence. Supplemental Material Methodology Forrester fielded its Q1 2014 Global Web Analytics Forrester Wave Customer Online Survey to 54 individuals who were current clients of the vendors included in our Forrester Wave evaluation. Each vendor was asked to supply a minimum of 10 customers, but not all vendors hit the threshold. For quality assurance, all respondents were required to provide contact information and answer basic questions about their firms revenues and budgets.
Gauging Web Analytics Practices In The Age Of The Customer 14 Forrester fielded the survey in January and February 2014. Respondent incentives included a copy of the published research. Exact sample sizes are provided in this report on a question-by-question basis. Panels are not guaranteed to be representative of the population. Unless otherwise noted, statistical data is intended to be used for descriptive and not inferential purposes. Endnotes 1 Forrester defines digital intelligence as the capture, management, and analysis of customer data to deliver a holistic view of the digital customer experience that drives the measurement, optimization, and execution of digital customer interactions. See the November 11, 2013, Digital Intelligence Replaces Web Analytics report. 2 When building out their digital intelligence teams, CI professionals should look to the gaming industry s ownership structures, which provide the staffing and organizational design to integrate the production of analytics with the business. See the April 27, 2012, Strategic Plan: The Digital Intelligence Playbook report. 3 For a comparison and state of the top web analytics vendors as they were in 2011 and as a useful baseline on how the practice has moved on since, see the October 6, 2011, The Forrester Wave : Web Analytics, Q4 2011 report. 4 A new kind of intelligence organization is emerging, combining disparate customer data teams into a consolidated customer strategy function. See April 29, 2011, Preparing For The Intelligent Enterprise: A Blueprint For Customer Intelligence Professionals report. 5 CI professionals need help to understand the technology, tools, and capabilities that comprise digital intelligence and the available vendor options for each category. See the April 3, 2014, Decipher The Digital Intelligence Technology Code report. 6 Voice of the customer (VoC) tools offers valuable qualitative insight that provides additional context to traditional quantitative analysis techniques. VoC capabilities take two primary forms: surveys that are proactively offered to visitors, and on-demand feedback forms for visitors to complete on their own. Example vendors representing this analysis category include ForeSee, OpinionLab, and Verint Systems. Interaction analysis tools are associated with session replay functionality, the ability to visually track visitor interactions with content and functionality. Example vendors representing this analysis category include ClickTale, ForeSee, and IBM Tealeaf. 7 Forrester had identified the top cross-channel attribution providers. See the April 30, 2012, The Forrester Wave : Cross-Channel Attribution Providers, Q2 2012 report.
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