Fliptop was a predictive analytics application combining public web data with internal CRM and marketing data to score leads, identify target companies and trigger marketing actions.
Fliptop was acquired by LinkedIn in 2015 and integrated with LinkedIn products. Fliptop is no longer available as a standalone product.
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Metadata.io
Score8.8 out of 10
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Based in San Francisco, Metadata.io is a Demand Generation and ABM platform designed to execute thousands of B2B campaigns in a matter of hours, automatically optimizing campaigns for pipeline impact at a high velocity.
1. Be sure to specify and understand the impact on your model when looking at volume versus value factors. 2. Ask all your potential vendors about set-up costs and time. 3. Understand, with any predictive model, how it will affect both marketing and sales - a predictive tool should bring the two closer together. 4. Remember - its predictive, not all-knowing and brief/train your teams accordingly.
Metadata is well suited when you have a really large ad budget (>50k per month at least). This is because the power of metadata lies in the ability to quickly set up and run a large number of experiments (combinations of channel, audience, creative, and conversion assets). To evaluate these variations, all of them need a large number of impressions, clicks, and conversions to be statistically relevant. If your budget is smaller, you will either have a very small number of experiments (not fully utilizing the power of metadata), or your experiments will not have enough clicks to make informed decisions. We had expected a better explanation of this from metadata before signing up.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A little more explanation of how different factors can affect the model in terms of the customer objectives - they've really listened here and have really focussed on the changes we needed to make.
Update specific fields/features e.g. multi-currency support (now done), non-confusing field names (being released), custom fiscal years for reporting (coming I believe)
If you don't have a large budget and audience it's hard to meaningfully optimize. If I have 4 ad creatives, to 2 audience groups on FB and LinkedIn, that creates 16 experiments, each of which needs an ample enough budget, say $40/day, that's now $640 per day or $19K per month.
Limited ability to edit ads after they've been launched. You usually have to stop the ad, clone it, and launch a new campaign.
Can't add new ads to existing campaigns which limits the ability to optimize. If I start an MD campaign with 4 ads, and in a few weeks we see that one is working well and the other 2 are not performing, I can pause those (or it can autopause by rules), but I can't add 2 more new creatives to the mix against the high performer. I'd have to either stop the high performer, and recreate it in a new campaign (losing likes and comments), OR - leave the high performer in the first campaign, and create. a second campaign with the new ones, which will only optimize against each other.
Limited to a single conversion event on a landing page. I'm not able to choose either a Demo Request OR a Sign-Up conversion, I can only choose one.
Google search ads are doable but aren't necessarily more feature-rich or easy-to use than native, so there's no value added to doing it through Metadata in my opinion aside from unifying ad reporting.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
We chose [Metadata.io] because it was a smaller company and could get more personalized attention. The price was better and they seemed more eager to support us. The feature set was what we were looking for and not more - it was exactly as robust as we needed it to be. Didn't want to pay for features we weren't going to use.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Huge decrease in CPLs, CPMQL and Cost Per Opportunity
Big improvement in MQL to SQL rates
90%+ of our leads from paid social now have valid business emails, before it was like 30%
Saving us hundreds of hours over the course of the next year doing daily manual optimization and budget management tasks for us so we can focus on strategy and testing new things
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
