QuanticMind Offers SEM Marketers Powerful New Automated Bidding Capabilities

QuanticMind announced its Spring 2019 product release, ushering in new functionality for digital marketers who are focused on achieving peak performance and optimization from paid search channels. The pioneering Martech company, based in Silicon Valley, has unlocked ways to automate highly valuable audience bid adjustments in Google Ads, optimize Bing Shopping campaigns using proprietary data science techniques, and launched a machine learning based forecasting module for SEM and Shopping campaigns. These new features together augment QuanticMind’s position as the leader in predictive digital advertising management.

“We’ve focused on adding sophisticated machine learning algorithms to ensure better accuracy and increased reliability in driving optimal performance of paid search campaigns,” said QuanticMind’s CEO, Chaitanya Chandrasekar. “These updates represent only the beginning of the journey we’re on to deliver a solution that enables digital marketers to solve paid advertising challenges at far greater scale, faster speed, and at deeper levels of granularity than previously possible.”

QuanticMind has committed to continually engage in product improvements to help digital marketers achieve their performance goals. This Spring release adds another chapter by delivering features that directly empower SEM marketers to optimize their marketing campaigns for the best ROI.

Read More: LumApps Closes $24 Million Funding Round Led by Idinvest

The highlight of the Spring 2019 release is the launch of Automated Audience Bid Adjustments for Google Ads. Sophisticated marketers understand the power of showcasing their ads to targeted audiences: who they are, their interests and habits, what they are actively researching, or how they have interacted with businesses in the past. The QuanticMind platform dynamically automates how marketers manage audiences in Google Ads by drawing on the historical performance of audience segments to set optimal audience bid adjustments. This new bidding model ultimately ensures that marketers are minimizing wasted advertising spend and maximizing their business returns by reaching the right people, with the right message, at precisely the right moment.

The second major capability rolled out is an advanced Forecasting Module. By taking in auction insights data, bid landscape models, historical performance trends, and seasonality factors, QuanticMind can now predict performance for up to 100 days in the future of paid search campaigns. By surfacing such critical insights in advance, marketers are empowered to determine what ROAS, Margin or CPA targets need to be set to achieve specific performance goals. Furthermore, channel budget shifts can be handled much more effectively with the guesswork eliminated.

Read More: Taulia Announces Partnership with Google Cloud to Solve Invoicing with AI

Rounding out the trio of major features is Bing Shopping Optimization. Now, the same powerful machine learning algorithms that QuanticMind applies to Google Shopping campaigns can be employed to drive better investments on Bing Shopping. Strategies and reporting across the two publishers sit directly in one source of truth, allowing for a holistic overview of performance. QuanticMind Shopping continues to support feed management for both the Google and Bing Merchant Centers.

The future of search engine marketing is bright as new levels of performance optimization become possible through QuanticMind’s Spring 2019 Release.

Read More: Gartner Says 49 Percent of Account Managers’ Sales Revenue Goals Don’t Distinguish Between Retention and Growth

Chaitanya ChandrasekarGoogle AdsNewsQuanticMindSearch Engine Marketing
Comments (0)
Add Comment