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Brick-and-Mortar Retailers Fight Back: Economist Intelligence Unit and APT

Brick-and-Mortar Retailers Fight Back

Based on a survey of over 250 global retail executives, this Economist Intelligence Unit and APT report explores how online competition is shaping traditional retailers’ strategies.
The Analytics Evolution - What's Next?

The Analytics Evolution - What's Next?

In this Information Age article, APT CEO Anthony Bruce shares his perspective on top emerging trends in analytics, including Machine Experimentation™, self-service analytics, and more.

The Discipline of Business Experimentation

Named a Harvard Business Review "Must Read for 2016," this article explores the keys to institutionalizing data-driven decision-making at leading organizations.
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Sales Impact of Online Auto Listings

Case Study: Measuring the Impact of Online Auto Listings

This case study describes how a leading automotive digital marketing provider used Test & Learn to run an experiment to attribute increases in car sales to its online listing services.

Optimizing Vehicle Sales Incentives

Case Study: Optimizing Vehicle Sales Incentives

An automaker used Test & Learn to test two versions of a dealer incentive program and target rollout of the best version to the most profitable dealerships, generating an $8MM incremental profit opportunity.

Marketing Innovations Don't Have to be Risky

Marketing Innovations Don't Have to be Risky

APT writes in DTC Perspectives about how pharmaceutical marketers can accelerate their innovation by rapidly testing their ideas, discarding the unsuccessful ones, and targeting to dial up ROI. 

Enhancing Non-Personal Promotion NPP

Enhancing Non-Personal Promotions

A guide to using in-market experimentation to optimize non-personal promotion investments. 

Thumbnail-FS-Improving Profitability within Payments

Improving Profitability within Payments: Test & Learn for Issuers

A leading credit card issuer used APT’s Test & Learn software to evaluate, refine, and target its credit card offers and marketing campaigns to those customers which were predicted to respond most profitably.