Advanced Machine Learning, Data Mining, and Online Advertising Services
At A.I. Optify, we run scalable marketing campaigns for B2B tech clients by using our unique and precise first-party B2B data and programmatic ad buying platform powered by machine learning algorithms.
In July 2015, a B2B startup company, TrustRank, reached out to us for help. The company wanted to plan a soft launch for their product to test a few hypothesis around their product/market. TrustRank provides a service for companies who are looking to hire a vendor providing them a special service such as public relations.
Let's say Apple is launching iPhone 7. They need to find a Public Relations firm helping them with news and media publications around the new release. The process of finding the right PR can be challenging and time consuming. TrustRank is providing a research tool to help B2B buyers find the right firm more efficiently than existing approaches.
TrustRank's busineess is a two-sided market where they need to target buyers (i.e. companies looking for B2B services) and vendors (i.e. B2B service providers) and onboard them on their platform.
TrustRank passed us their creatives, landing pages and a high-level descriptions for buyers/vendors firmographics that they want to tareget. A few segments for buyers/vendors firmographics are shown below:
|Tech Companies||Buyer||Los Angeles, San Francisco, New York, Chicago etc.||NA|
|PR Firms||Vendor||Los Angeles, San Francisco, New York, Chicago etc.||NA|
|Marketing Firms||Vendor||Los Angeles, San Francisco, New York, Chicago etc.||NA|
|Advertising Firms||Vendor||Los Angeles, San Francisco, New York, Chicago etc.||NA|
When planning the campaign for TrustRank, we quickly realized a few challenges. The first being how/where we could find/target buyers and vendors, bring them to TrustRank LP's, and take them down the product's funnel.
Next, the strategiesi/channels for targeting buyers are different from the ones for targeting vendors because of the episodic nature of buying process and the long B2B buying cycle. Specifically, it's not possible to target buyers only based on their firmographics. You need to find them early on when they are in their research/buying cycle. Last not the least is the optimization startegies to find/target high-values users with optimal economy.
The top challenges are finding the right signals to target vendors and also targeting B2B buyers when they are in their research/buying cycle.
To address above challenges, we ran multiple campaigns exploiting different channels such as: search advertising, scalable display advertising by talking to multiple exchanges, B2B-tuned audience display advertising, and retargeting.
We integrated our programmatic ad buying platform with Google Analytics so that we could measure users interactions with the client's product and use that data to continue optimizing the ad buying process at different levels such as: bids, ad copies, audience segmentats (i.e. media/user attributes) etc.
This is still an ongoing campaign and the client is happy with the results. See below for a few examples of companies firmographics and contact demographics of high-qualified leads that we nurtured down the funnel for TrustRank:
|Type||Company Industry||Geo||Company Size||Contact Seniority||Contact Job Title|
|Buyer||Internet||San Francisco, CA||51 - 200 EE||VP||VP Business Development|
|Vendor||Public Relations and Communications||San Francisco, CA||51 - 200 EE||Manager||Office Manager|
|Buyer||Financial Services||New York, NY||51 - 200 EE||CXO||CEO/Owner|
|Buyer||Event Services||Schiller Park, IL||5001 - 10000 EE||Director||Director of Communications|
Our machine learning algorithms constantly explore new audience segments, prune the non-performing ones, shift the campaigns' budgets towards the most-performing segments, and optimize the CPM/CPC bids to minimize CPA for getting high-value leads.
To learn more about our computational Advertising and Marketing services, you can contact us at: email@example.com