Yield management best practices guide

Yield management is the strategic process of carefully selecting and prioritizing viable survey opportunities to ensure that the highest-performing studies receive the most traffic, while surveys falling below desired metric thresholds are either deprioritized or not considered at all.

This content has been updated to reflect our latest pricing model, replacing cost per interview (CPI) with revenue per interview (RPI) metrics. We will be working closely with our supply partners to transition them to the RPI model. If you have not yet migrated to RPI and require access to documentation containing CPI details, please contact your account team, who can provide the relevant materials.

To help our supply partners build out an effective yield management system we recommend applying the following approaches, amongst a few other considerations. This content is not relevant for our Match Integrated partners.

• Creating suitable survey filter rules

• Identifying viable surveys

• Ranking eligible surveys

• Pacing survey entrants

• Tracking survey performance

• Shutting down poorly performing surveys

• Building a testing framework

Creating suitable survey filter rules

When starting out your integration it is important you monitor if any initial survey filtering rules applied to your feed opportunities subscription or within your own system are heavily restricting the survey inventory available. Having a significantly reduced pool of surveys to match users with can impact potential earnings.

A recommended best practice is to keep your survey filtering criteria broader during the soft launch phase. As you gain a better understanding of how your respondents perform against different survey types, length of interview (LOI), buyer preferences etc, you can gradually refine and test your survey filtering rules to optimize performance. See here for more information on creating a testing framework.

Feed opportunities allows you to easily adjust the criteria for surveys you receive notifications about, simplifying the process of gradually filtering out surveys that are not relevant to your specific business model. By adopting this approach, you can adapt and tailor your survey selection process to align with your users' preferences and maximize your survey-based revenue.

Example survey filtering criteria

Opportunities subscription

{
    "callback" : {{callback}},
       "opportunities": [{
            "country_language" : {"in": ["eng_gb", "eng_us"]},
            "length_of_interview": { "lte" : 20 },
            "conversion": { "gte" : 0.05 },
            "revenue_per_interview": { "gte" : 0.50 },
            "study_type": {"in": ["adhoc", "recontact"]}
     }]
}

Identifying viable surveys

Before presenting the best survey opportunities to your respondents, it's crucial to ensure that the following criteria is met:

• The survey is still live

• The total quota is available

• Any subquota(s) matching respondent profiles is available

• Data profiled on a respondent meets the qualification criteria

• Respondent has not attempted this survey before

• Respondent has not attempted a survey in this survey group before (if applicable)

Ranking eligible surveys

Cint provides a comprehensive set of data through our APIs and redirect information, empowering suppliers to target the most suitable and high-performing surveys. To assist you in effectively utilizing this data, we've compiled a list of what we consider to be crucial data points when creating a survey ranking algorithm.

Please note some of these metrics should be used as a starting point for assessing the overall health of surveys from a global perspective, it's essential to track your internal performance as you direct respondents to surveys.