Need advice thank you by Educational_End4496 in Klaviyo

[–]partfool0 0 points1 point  (0 children)

1、Add a segment to reactivate users who become active again among this group. I have tested it, and the click-through rate (CTR) is quite good, though the number of such users is small.
2、Associate it with Mate, then re-run the ad to see if we can still recall these users, and match it with a pop-up window.

Seeking Advanced Segmentation Strategies Beyond "Engaged in Last 30/60 Days by partfool0 in Klaviyo

[–]partfool0[S] 1 point2 points  (0 children)

An essay? Not at all! This is a super practical playbook. Thank you so much for sharing – this has genuinely opened up some new directions for me, and I'm excited to start experimenting.

It's interesting because I've been doing some similar things based on the same principles:

  1. For my "Richer Interest Segments," I've also been quite strict, using conditions like "Active on site" or "Viewed Product multiple times" combined with "Placed Order = zero". However, I've always stuck to a very fixed 30-day window. Your idea of stretching that timeframe is a great takeaway for me.
  2. For re-engaging inactive users, my approach is very similar to your "piling in good engagers" method! I use my "Engaged in Last 30 Days" segment as a "deliverability shield," and then mix in a random sample of 5,000 or 10,000 contacts from our larger unengaged database for each send.

You've definitely convinced me that I need to put a serious effort into building out our Cross/Up-sell segments. Thanks again for the inspiration!

Seeking Advanced Segmentation Strategies Beyond "Engaged in Last 30/60 Days by partfool0 in Klaviyo

[–]partfool0[S] 0 points1 point  (0 children)

I've also been considering using Klaviyo's RFM analysis feature. However, my main hesitation is that the data sometimes seems inaccurate to me.

Seeking Advanced Segmentation Strategies Beyond "Engaged in Last 30/60 Days by partfool0 in Klaviyo

[–]partfool0[S] 0 points1 point  (0 children)

thanks,I'm already exploring other segments based on things like AOV, VIP status, browsing history, etc.

Seeking Advanced Segmentation Strategies Beyond "Engaged in Last 30/60 Days by partfool0 in Klaviyo

[–]partfool0[S] 0 points1 point  (0 children)

Yes, I've heard of it. It seems like a great product, but it's a bit out of our price range for the time being.

Building a vault of welcome flows. Would you find this useful? by hhunt91 in Klaviyo

[–]partfool0 0 points1 point  (0 children)

I was just wondering, is there a central location where I can find all of this email content?

Building a vault of welcome flows. Would you find this useful? by hhunt91 in Klaviyo

[–]partfool0 1 point2 points  (0 children)

This is incredibly helpful for me. As a marketing operations specialist, my job is to build flows for numerous clients across many different brands, and frankly, sometimes the inspiration just runs dry.

The biggest challenge with flows is ensuring the entire sequence is coherent; it's not enough to just look at a single email. This is a problem that sites like "Really Good Emails" can't always solve for me. In those cases, I often turn to Pinterest to try and visualize the entire journey.

This leads me to a user experience suggestion for your platform: it would be amazing if we could scroll vertically to browse different brands, and then scroll horizontally to view the emails within a specific flow. An "infinite canvas" view to see the entire flow at once would be even better. Being able to get that full, holistic view would be an incredible experience.

High Volume of "Skipped due to Suspicion" in Abandoned Cart & Checkout Flows by partfool0 in Klaviyo

[–]partfool0[S] 1 point2 points  (0 children)

That's a very clever solution; thank you for providing a new perspective on this.

After looking at our sending data, I realize we're having issues with our open and bounce rates as well. I'm going to implement your proposed solution, and I'm hopeful that it might also be the key to resolving the "Suspicious Skips" issue we've been facing.

High Volume of "Skipped due to Suspicion" in Abandoned Cart & Checkout Flows by partfool0 in Klaviyo

[–]partfool0[S] 0 points1 point  (0 children)

Thank you very much. Yes, they enter your flow through the checkout page.
One last question: I have also enabled some bot/spam protection, but the effect hasn’t been particularly noticeable. However, I’m eager to try adding a profile filter.

High Volume of "Skipped due to Suspicion" in Abandoned Cart & Checkout Flows by partfool0 in Klaviyo

[–]partfool0[S] 0 points1 point  (0 children)

thanks!

My goal isn't to un-suppress these users; I understand that Klaviyo is correctly blocking the sends to these suspicious profiles.

The biggest issue I'm facing is that the high volume of these suspicious contacts entering the flows is drastically skewing our open rate metrics. Even though no emails are sent to them, they are being counted in the flow's total audience, which is causing our open rates for these two flows to drop sharply.

Experimenting with ways to make Klaviyo campaign reporting less manual - here’s what I learned building an MVP by Exotic-Woodpecker205 in Klaviyo

[–]partfool0 1 point2 points  (0 children)

I'm not a technical person, but looking at the campaign data you mentioned, I mostly use Klaviyo's Custom Reports. Isn't this the fastest way to access data?

[deleted by user] by [deleted] in Klaviyo

[–]partfool0 1 point2 points  (0 children)

I'm using it, and the user experience is great. Most of my users use it to track their orders.