2022 - February Release

 

 

 

 

 

 

Dynamic Contacts from Salesforce

We are introducing a new Audience in platform that will allow customers to target their audience in contact level.
From their integrated Salesforce instance, platform will be able to extract contacts and push that information to the integrated advertising channels.

The contact list is generated by querying contacts directly from Salesforce and then it is enriched with Metadata Metamatch data.

New Query builder!:

As part of this release, we are introducing a new and powerful Query Builder which can combine multiple types of information to improve the quality of the targeting by adding granular filtering to the queries.

Queries now can combine data between “Accounts, Opportunities & Contacts”

Note. Lead objects are currently not able to be combined into a single query and needs to be used as separated query.

Dynamic Refresh:

This audience can be set as Static or Dynamic, which refreshes daily to get the most accurate data from Salesforce.

 

 

 

E-Commerce targeting

New options are available for some of our audiences to improve the quality of our targeting when the focus is on e-commerce industry.

Slintel Technographic:

This audience now has firmographic filters to narrow the targeting by:

  • Employees

    • Choose the amount of employees your targeting company has

  • Industry

    • Narrow the technology targeting by defining the industry of your targeting audience.

Facebook Native Criteria:

It now includes options to filter audience by:

  • Interest

    • Select any native interest available in Facebook datasource.

  • Age Range (21-65+)

    • Narrow the audience based in age.

 

Customizable Attribution Models

Previously, customers could only customize Triggered and Influenced attribution models which significantly limited their ability to play around with different attribution logic and see what works best for them. With this release, we will allow them to customize any of our 5 pre-defined attribution models, thus turning opportunity summary into experimentation hub and giving customers greater control over the way they connect pipeline numbers with ads campaigns.

How this feature works:

  • Attribution Models tab has been removed from the Library.

  • On the Opportunities Summary report users can now see which model is used to define Triggered, Influenced, or Impacted opps

  • Directly from the report users can customize any model (with the exception of Clicks model) by changing relationship type, attribution window, and giving a new name to the model.

 

Opps counting improvements - Performance by channels

When filtering Performance by Channels report by date range, Opps stats will be filtered out based on the Leads converted dates. I.e. if the experiment has 5 leads during the selected period of time, only the Opps of those 5 leads will be counted in the report.

 

 

Optimizer post processing and improvements (LG)

Lead Generation optimizer becomes more reliable.

In the latest update we added additional stage before budget allocation. All numbers are rounded, edge cases with keeping total group budget are covered.

The budget will be not updated if the delta change with previous budget is small or zero.

 

 

Auto-Pause/Auto-Restart due to (not) enough group budget (LG)

Lead Generation optimizer becomes more self-sufficient.

There are cases when during the allocation we go over group budget and assign extra budget to underperforming experiments and as a result best performered experiments strugling with not enough budget.

During budget allocation if the total allocated budget is above the remaining budget we will pause the worst experiments. However, they will have second chance on the next Optimizer run. If there are downgraded in performance experiments on the next run, previously paused experiments will be automatically restarted.

The final goal is to have more Leads in total.

 

Daily Budget & Pacing Calculation

Daily Budget and Pacing calculation becomes more precise.

Our research shows that channels don’t store historical daily budget information. However it’s vital to analyze historical pacing and stats.

In the current release we improved our historical daily budget calculation and took into account daily budget changes by a minute.

 

Auto-Pause due to Monthly Cap met

Spend more with group, but stay in safe mode and don’t overspend.

Finally the main problem with Auto-Pause due to Monthly Cap met was figured out and we can increase the pause threshold to 99%.

The channels give us the latest experiments performance with the delay and we might miss the momentum to not overspend. We analyzed the hourly data flow and made our calculations more inteligent, which covered data delay.

The feature still will be under our intendance in order to have the best balance for the group budget.

 

Our recently launched new channel - Google Ads, got a new additions to the core functionalities, as follows:

Callout Extensions:

  • Ad extensions add up to 15% higher clickthrough rate by showing additional information on ads, giving people more reasons to choose your business.

  • Callouts are small descriptions that are append at the end of the description of Search Ads

  • All callouts added to Metadata platform will be displayed within all Google Ads campaigns

Keyword Match type

  • It is now available the ability to define Keyword Match type per campaign

  • This option is available in campaign wizard and it can be edited at experiment level.

 

New Native Campaign Objectives for Brand Awareness

We are improving the quality of our brand awareness campaigns by pushing different objectives based on the type of Ads selected in Campaign Wizard

Video Ads

  • Platform will push Video views objective on channels.

Image Ads

  • Objective on channel will be set as Engagement.

Those changes will improve the quality of information we collect from channel, which will allow further improvements in our optimization.