Digital is changing the way that organizations need to interact and engage with their prospects and customers. Most organizations determine the effectiveness of their digital efforts based on conversions - but what happens after that conversion? According to a recent SiriusDecisions report, 80% of B2B marketers indicate that they will be using digital advertising in 2017, but less than 50% are measuring ‘beyond the click’.
In order to have a truly effective digital strategy, organizations must look even further. By measuring ‘beyond the click’, organizations gain the ability to personalize the entire customer journey, engaging people at every touch point.
In this webinar with leading global B2B research and advisory firm SiriusDecisions, and Acquia Partner Inviqa, we’ll cover the tactics to optimize your personalization strategy, including:
-The rise of digital advertising and the need for ‘beyond the click’ measurement
-The need for web personalization and how to implement it in your digital strategy
-Different methods of personalization and best areas to personalize
-Best practices to follow and what to watch out for
Not provided is a grouped Google SEO results, so you don’t know where people are coming from
SD 2015 Buying Study NA and EU, 1005 respondents who recently involved in tech purchase 85% involved within 3 months Buying interactions instead of buying preferences What they did, what role they played, where they were in the buyers journey, really powerful What were the interactions and how many interactions were there (exchange of information)
How well are these tactics tied together??
Digital touches: searched for info online, filled out a form, viewed a webcast, visited company website, analyst review online, online community Human touches: Met with rep onsite, trade show, user group meeting, onsite demo
Advertisers need to measure all classes of ad tactic performance in order to identify areas to test and improve impact on demand creation. Using the SiriusDecisions Aligned Measurement Framework (see brief), digital advertising measurement can be grouped into 3 categories: •Advertising. Metrics include impressions, cost per mille (CPM) impressions, clicks, or cost per click (CPC). These metrics typically fall under the activity class within the Aligned Measurement Framework and quantify what was done. In addition, the metric for Impressions could also be categorized within the readiness class, as the number of available impressions for a target is important to understand how prepared an organization is to perform. More than half of organizations surveyed focus their measurement within this category. •Website. Metrics include website visits, bounce rate, time on site and from conversion. Aside from conversion, these metrics also fall under the activity class and are useful to quantify what was done. However, conversion begins the transition to output, or measuring the result of the activity. Measuring conversions allows marketers to understand top of funnel impact and begins the transition beyond the click. •Waterfall. Metrics include MQL, SQL and Close Won (see core strategy report: The Sirius Decisions Demand Waterfall Implementation Guide). Similar to conversions in the Website category, MQL and SQL are output metrics, with Close Won falling into the impact category and quantifying the effect of the output against business goals (revenue generated). Metrics at each stage are important in determining digital advertising program. However, in order to optimize upstream advertising and website performance, Waterfall metrics should be utilized to give visibility into true output and impact performance for digital advertising.
Explicit personalization. This type of personalization relies on data provided directly by the user to determine what content and interactions should be presented. Because users must provide information themselves, this type of personalization is most useful for well-defined segments where users can easily provide the identifying data in a reasonably consistent way. Typical types of data used include title, role, company, industry, and geography. Explicit personalization is supported by a wide range of technologies, including CMS and MAPs. Of the types of personalization, it is the simplest to deploy, but success requires an ability define the segments and the rules to determine what content to show, and validate the information provided and the overall quality of the targeted content.
Implicit personalization. Implicit personalization, which represents the next level of personalization, is often deployed in addition to explicit personalization. This type of personalization relies on tracking user behavior across a wide variety of marketing vehicles to infer what type of content to present to the user. Because this type of personalization relies on a wide range of data collected without the users’ direct input, it can build a more complex picture of a user. This picture can be used to personalize on characteristics that are more complex and less defined than explicit personalization – including segmenting by stage in the buying cycle, interests or business need. These qualities make it extremely useful for companies looking to drive progression or create opportunity based on complex circumstances. Compared to explicit personalization, implicit personalization requires more complex technology that can collect and analyze a stream of heterogeneous data from multiple sources. Many – but not all – CMS and MAPs support this technology. Therefore, it is important to determine how current or proposed systems can provide this capability. Marketers must also be able to create insight from this data in order to define and refine segments and create relevant content and interactions. Doing so requires the ability to work with large data sets and the use of statistics to determine relationships and correlation. For companies without this capability in-house, agencies or service providers can fill this need.
Augmented personalization. This type of personalization, which uses data that does not come directly from the user to drive personalization decisions, represents the most advanced form of personalization. It includes data from third-party sources, such as LinkedIn, and other demographic and behavioral data sources. With this data, the user profile can be expanded to provide more information that can be used to present more targeted content and interactions. When used in conjunction with explicit and/or implicit personalization, augmented personalization can increase the accuracy and speed that relevant content can be delivered. While this type of personalization has clear and obvious benefits, it has steep requirements for deployment: It requires technologies that can support explicit and implicit personalization and integrate additional data seamlessly with the data collected directly. It also requires a source of useful and reliable third-party data that can provide relevant information on Web site visitors. While these technologies and data are available, finding and selecting them can be challenging given the relative immaturity of the market. Care must be taken that the organization’s technology, process, people and skills are ready before this type of personalization is deployed.
Most popular stories are in the top view
Many more categories are further down
Most popular stories are in the top view
Acquia Lift’s approach is different- with the goal of driving conversions faster than ever before. Starting with data collection, the marketer is able to gain insight into their individual audiences based on displayed actions and behaviors. With content hub built in the core of the solution, all relevant content is easily discovered from multiple sources. Through Lift’s experience builder, marketers are able to set rules to ensure the right content is delivered to the right people at the appropriate time in their journey. Now as buyers engage with a brand across various devices and channels, they are receiving the most personalized experiences, again shortening the sales cycle and generating bottom-line results.
So how does this all work exactly? Lift automatically captures and unifies data across web properties for both known and unknown users. As the visitor identifies themselves through a form submit, the previously anonymous data merges with the known information. Data can be exchanged bidirectionally across various channels through the flexible API. Or through a prebuilt Marketo connector, data is easily pushed into Lift. The right content is matched with right segments based on the specified rules. These personalized experiences are then delivered to the customer on their preferred device. Unlike other solutions that focus primarily on testing, Lift offers a/b testing while focusing on the importance of rich data collection and content distribution.
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Going Beyond The Click: The Importance of Web Personalization