Ashwin Sande is Product Manager and self-proclaimed Chief Fun Officer at Factors.AI. He’s had years of experience in performance marketing, product marketing, and marketing analytics. Rahul Danak is a customer success manager at Factors.AI, and like Ashwin, is well versed with all things performance marketing and marketing analytics. Here are a few excerpts:
Q1) We’re an early-stage B2B start-up and have been trying to re-market on Google ads using our account list. What we’ve noticed is that when we upload our list of sales prospects on Google ads, the percentage of people that Google matches is extremely low. What can we do to fix this?
Ashwin: Google account matching issues are pretty common. Here are a few solutions we’ve tried with varying degrees of success in the past:
Q2) We’ve been investing heavily in Google ads recently but we've hit a glass ceiling around the quality scores of our search ads. Any ideas on how we can optimize for this?
Rahul: First, always make sure your ad copies are of good quality. Next, drill into your landing page — technical aspects, page loading times, content structure, and anything else that might be causing an issue. You can also look into customising your landing pages and banners based on various use properties including location, source, medium, device, and more.
Q3) When would you say, in terms of google campaign metrics, is the best time to switch to a more sophisticated DDA attribution model?
Ashwin: Firstly, and I’m sure it’ll improve with time, but DDA on Google analytics isn’t very robust. With that said, if your lead volume is at least 150 leads/month, it’s worth moving to a multi-touch attribution model. These models usually require a minimum amount of data to provide meaningful conclusions. I’d say clicks and impressions don’t play as big a role as the number of leads you’re receiving. It also helps to keep an eye out for leads across channels — organic traffic, LI ads, G2 ads, etc and perform attribution modelling across these touch-points.
Q4) We currently use single keyword ad groups for the North American market. We’re trying to expand this to other regions and geographies as well. How would you recommend restructuring the original campaigns?
Rahul: Maybe not initially, but after a few weeks of data collection, a staggered approach might help optimise ad spend and mitigate investment risk. Look for surges in keywords, copies, and content using A/B tests in specific regions as well.
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