Filter by "Opted Out Text" actually show those who opted out, not just those who opted in
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Morgan Luna
Currently when adding the "Opted Out Text" filter it shows everyone who has not opted in, not just customers who replied to the text and opted out. When looking at efficacy of lead sources this is an important factor and a tedious one to have to manually track. The filter should do what it says and show customers who have opted out of texting.
Shelby Parker
Great to hear your perspective, Morgan Luna! I have a few more questions for you:
- Can you provide examples of how the current filter results impact your workflow or decision-making?
- How frequently do you need to use the 'Opted Out Text' filter in your analysis?
- Are there any specific scenarios or reports where having accurate 'Opted Out Text' data is critical for your operations?
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Morgan Luna
Shelby Parker
- The current filter impacts our workflow because it does not accurately identify customers who have explicitly opted out of text communication. Instead, it groups together customers who never opted in with those who actively opted out. This makes it difficult to evaluate the true effectiveness of texting by lead source and requires manual tracking to determine actual opt-out behavior, which is time-consuming and prone to error.
- For internet managers, BDC managers, marketing managers, and even sales managers this would likely be used on a weekly basis to track lead source and communication efficacy.
- Accurate “Opted Out Text” data is critical when analyzing lead source efficacy, adjusting outreach strategies, and reporting on customer communication preferences. Being able to clearly distinguish between “never opted in” and “actively opted out” would significantly improve reporting accuracy and operational efficiency.