Understanding paid tactics
Paid tactics are recommendations Paid Media Manager generates for each ad collection (known as an ad set in Facebook Ads and an ad group in Google Ads). The recommendations indicate whether a particular tactic is likely to be successful for the specific ad set or group, for example, whether excluding ineligible individuals is likely to increase the performance of that ad.
The strength (that is, effectiveness) of a tactic is estimated by associating each paid ad collection with a matching action in Pega Customer Decision Hub, and then checking how the action performs against the strength criteria of the tactic.
Supported paid tactic types
Paid Media Manager provides the following out-of-the-box ways of leveraging next-best-action decisioning to optimize advertising on paid channels:
- Optimizing for omni-channel conversions
- Optimize your advertising spend for real omni-channel conversions, rather than clicks or impressions.
- Reducing ad spend
- Reduce wasted ad spend by preventing ads from being shown to ineligible individuals.
- Cross-sell and up-sell
- Increase your cross-sell and up-sell with first-party AI data derived from the history of the individuals' interactions with your organization.
- Prospecting with first-party data
- You can also leverage the same highly granular AI data to find lookalikes of your existing audiences and target them as prospects.
Paid Media process overview
Implementing the paid tactics enables various teams to work together in new ways to enable these powerful tactics. Typically, these include data science, IT, and advertising operations.
| Role | Description | Required access | Typical tasks |
| Paid specialist | The paid specialist is a marketer who uses Paid Media Manager to discover opportunities to optimize ad spend on advertising platforms. |
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| Ad strategy and operations | The ad strategy and operations team manages advertising campaigns in various platforms such as Facebook Ads, Google Ads, or LinkedIn ads. |
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| NBA specialist | The NBA specialist works to fulfill the business-as-usual change request based on the details provided. |
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First, the paid specialist uses Paid Media Manager to discover opportunities to optimize the ad spend by using the results of next-best-action decisioning in the destination platform. The paid specialist then works with the ad operations team, who have access to the ad account in the destination platform, as well as with Customer Decision Hub NBA specialists, to implement the recommended improvements. The diagram below outlines the process flow and required user roles.
Reviewing the recommended tactics
Paid specialists use the Paid Tactics landing page in the Pega Customer Decision Hub portal. Paid specialists access the landing page by clicking in the left navigation menu.
The Paid Tactics landing page displays various information about the ad collection, such as the collection name, campaign, campaign budget, and so on. It also displays the following information that is specific to Pega Customer Decision Hub and Paid Media Manager:
- Data
- The name of the artifacts that will be created in the ad network after the tactic is applied.
- Data status
- The current status of the tactic:
- -- - The recommendation has not been applied or the Pega Customer Decision Hub configuration change has not been requested yet.
- GENERATED - The recommendation has been applied and artifacts have been generated in one of the ad networks.
- DELIVERING - Artifacts have been generated in the ad network.
- CONFIGURED - Artifacts have been generated and configured in the ad network.
- Strength
- How successful the tactic is likely to be, based on the underlying data.
- Connection capable?
- Yes or No based on the Availability rule defined.
You can adjust the information that is displayed on the page by using the Fields button to add or remove columns from the table, and then save your changes as a new view. For example, you can create a view that shows the results for only the NBA Lookalike Targeting tactic to see which ad collections have the highest potential.
Conversion Bid Optimization tactic
This tactic determines which ad collections offer the most significant opportunities to optimize bidding based on conversion events. Use it to understand the rate of conversions for an ad collection based on the linked action and the amount of spend that the ad group generates.
The strength of this tactic for a particular ad collection is derived from the average acceptance rate for the linked action over the last 30 days.
Conversion Bid Optimization tactic
| Tactic strength | Average number of accepted offers for the last 30 days |
| HIGH | Higher than or equal to 10,000 |
| MEDIUM | Between 10,000 and 1,000 |
| LOW | Between 1000 and 400 |
| NOT RECOMMENDED | Lower than 400 |
Conversion Lookalike tactic
This tactic surfaces opportunities to optimize the ad budget by targeting individuals similar to those that have already converted, that is, accepted an action that was delivered to them by Pega Customer Decision Hub. Understand the number of individuals that have converted for an ad, based on the number of accepted offers of the linked action.
The strength of this tactic for a particular ad collection is derived from the number of accepts for the linked action.
Conversion Lookalike tactic
| Tactic strength | Number of accepted offers |
| HIGH | Higher than 1,000,000 |
| MEDIUM | Between 1,000,000 and 100,000 |
| LOW | Between 100,000 and 1,000 |
| NOT RECOMMENDED | Lower than 1,000 |
NBA Known Targeting tactic
You can use this tactic to see the most significant opportunities to target known individuals by prioritizing for targeting the largest number of individuals that are eligible for the linked action. View and understand the status of each priority bucket for the linked action, that is, for individuals who have very high, high, medium, low, or very low priority for the action.
The strength of this tactic for a particular ad collection is derived from the number of individuals eligible for the linked action, as well as the mean variation in the distribution of the action priority among the individuals.
NBA Known Targeting tactic
| Tactic strength | Number of eligible individuals | Mean variation |
| HIGH | Higher than 5,000,000 | Higher than 50% |
| MEDIUM | Between 5,000,000 and 500,000 | Between 50% and 25% |
| LOW | Between 500,000 and 5,000 | Between 25% and 50% |
| NOT RECOMMENDED | Lower than 5,000 | Lower than 10% |
NBA Lookalike Targeting tactic
You can use this tactic to see the most significant opportunities to find new prospects by prioritizing for targeting the largest number of individuals that are eligible for the linked action. View and understand the status of each priority bucket for the linked action, that is, for individuals who have very high, high, medium, low, or very low priority for the action.
The strength of this tactic for a particular ad collection is derived from the number of individuals eligible for the linked action, as well as the mean variation in the distribution of the action priority among the individuals.
NBA Lookalike Targeting tactic
| Tactic strength | Number of eligible individuals | Mean variation |
| HIGH | Higher than 5,000,000 | Higher than 50% |
| MEDIUM | Between 5,000,000 and 500,000 | Between 50% and 25% |
| LOW | Between 500,000 and 5,000 | Between 25% and 50% |
| NOT RECOMMENDED | Lower than 5,000 | Lower than 10% |
Negative Audience tactic
This tactic optimizes your ad spend to prevent ads display for ineligible individuals. You can see which ad collections have the largest negative audiences (that is, individuals who are not eligible for the linked action), alongside the amount of ad spend that they generate.
The strength of this tactic for a particular ad collection is derived from the size of the negative audience, that is, the number of individuals that are ineligible for the linked action.
Negative Audience tactic
| Tactic strength | Number of individuals in the negative audience |
| HIGH | Higher than 1,000,000 |
| MEDIUM | Between 1,000,000 and 100,000 |
| LOW | Between 100,000 and 1,000 |
| NOT RECOMMENDED | Lower than 1,000 |
- Associating actions with ad collections on paid destinations
Before a paid specialist can view the recommended tactics for an ad collection, they first associate the ad collection with an action in Pega Customer Decision Hub.
- Requesting business-as-usual updates to paid configuration
After reviewing the recommended tactics, the paid specialist communicates the recommendations to the advertising team, and then request the necessary configuration changes from an NBA specialist.
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