Ad Hoc Engagement Metrics

Expanding ONEcount to consume additional data types

ONEcount has defined “silos” for three different types of engagement data: email, banners and web pages. For each silo, there are well-defined, industry-standard metrics to measure performance.

For example, email is measured with opens, clicks, bounces. Web traffic is measured with page views, Banners are measured in impressions and clicks.

Each of these engagement “events” have different metric criteria, based on what the silo is.

You can also use ONEcount to capture, segment and report on other types of engagement data. Data for webinars, in-person events, trade shows, conferences using ONEcount’s ad hoc Engagement Tool.

This tool allows you to create your own engagement silos using the exact points and metrics that are relevant to your business.

For example, say you want to track and report on webinars. Your business may get paid based on the number of completions—people who complete the webinar. Or you may get paid based on how many people show up. Or how many people watch more than 10 minutes of the webinar. Often these factors are based not just on your business practices, but also on the capabilities of the webinar vendor you are working with.

ONEcount’s Engagement Tool allows us to create an engagement silo for this data, and use the specific metrics that work for your specific business. What’s more, you can create multiple engagement silos with completely different metrics to support multiple business units, or multiple webinar vendors.

For example, you may hold webinars with On24, which reports attendance, completions, attendance time, etc. You may also hold webinars with Zoom, which reports completions and questions asked, but not attendance or time.

With ONEcount, you can choose to create a single engagement silo for “Webinars” that includes data from both vendors, or you can create two enagement silos, one for On24, and one for Zoom. The choice is yours.

Creating Engagement Metrics

Here you can see an example with three different types of adhoc engagements: The client’s internal lead generation system (LCS), data from an Omeda email click report, and data for the client’s in

person events.

Each engagement silo has its own unique metrics. These metrics can be used as search criteria in the List Wizard, as criteria for segments, and they can be used in ONEcount BI to develop custom charts and graphs—building charts showing event attendance year over year, for new leads for advertiers. Once you create a silo, the individual metrics are determined by you, and you can have as many metrics as you would like.

For the LCS metrics, the client has created a number of metrics that pertain to this type of engagement, including the asset that is being used for lead generation, the topic, the web site the lead came from, etc. The only metrics that are required for each engagement silo is the ID, which is assigned by the system and can not be edited, the activity time, this is when the engagement happened, and the name, which is the name of the engagement activity. These three items can not be edited or deleted, however you do have some flexibility in terms of the name.

The engagement name is comparable to the email campaign name in an email engagement, or the web page url in a web engagement. It is the main identifier for this type of behavior.

Since the engagement name is used as an index and search criteria, it’s important that it not be too varied. For example, having 1,000,000 different seminar names could make it difficult to search effectively in the back end, and make segmentation difficult. Therefore, you can change the metric name to a Select type of metric, so there are a small number of events to choose from.

When defining a metric, you have different metric types to choose from:

1) Checkbox: this provides multiple responses (ie., what products do you specify)

2) Numeric: this allows >=< searches

3) Select: Pick one (Job Title)

4) Text: This can be searched with string matches

Currently the only time-based metric is the activity date/time. This is because an engagement metric refers to a specific event, and the activity date/time is when that even occurred.

How To Use Engagement Metrics

When creating engagement metrics, think about how they will be used for querying, segments and analytics.

In the List Wizard, you can include and exclude metrics. There will be a pull-down allowing you to select an engagement silo. When you select a silo, the “target” box will pre-populate with the names of your engagements. You can also Select All. You must choose at least one metric name.

Once you select the target, you can choose the various metrics you want to include, as well as possible values:

When defining a segment, you can choose the metrics you want in the segment. First pick the engagement silo under “category”, then the specific metric and values:

Engagement Metrics in ONEcount BI are typically custom charts. When your account is first set up, your ONEcount team will help you build your initial engagement metrics, as well as any analytics screens you need to use your data. You can of course customize the data and build your own charts as you see fit.

Important Notes:

When you define metrics, there are a couple of things to keep in mind:

1) Engagement silos connect activities to users in your database.

2) Engagement activities are not summaries (ie., 34 clicks, 27 opens). They are specific events tied to a specific user in your database or a specific anonymous user.

3) An engagement event is just like a web page view, an email open or a banner click: in addition to the metric info, you will need to insert the identifying user data along with the engagements

4) Even though engagement data is tied to users, you do not need to define user data as part of the engagement (fields like email address, job title, etc., are typically demographics fields and would not be defined in an engagement)

5) HOWEVER, any data that might otherwise be demographic data that is uniquely tied to the engagement event can be added to the engagement For example, for a trade show event, “What products are you actively looking for?” might be a demographic, but in the context of a trade show, might result in different answers depending on the show the user is attending.

4) Engagement data can only be inserted using an DExTR/Import job, or via the API