ACQUISITION

Reduce your expenses while effectively converting potential leads

Our approach integrates data, analytics, intelligence, consultation, and campaign execution services, ensuring a consistent acquisition of valuable new customers.

Acquire new and profitable customers quickly and effectively

Our acquisition solutions combine the best of our data, intelligence, consulting, campaign execution and analytics services to lower your cost per acquisition, increase new customer volume, and ensure we are adding profitable customers with high lifetime value to your customer base.

Stop Chasing Cost per Acquisition

Most companies measure the success of their acquisition programs in terms of cost per acquisition (CPA) and the number of new customers acquired. But these metrics can be misleading. If a client sets an acquisition goal of a $10 CPA and 1 million new customers per year and achieves an $8 CPA and 1.2 million customers, their program looks like a success. But what if those new customers spend less and have a much higher than average attrition rate?

Unlock growth opportunities and expand your horizons through strategic acquisition.

Start Measuring CPqA: Cost per Quality Acquisition

We aim to succeed. To do so, we use CPqA as our key metric – Cost Per “Quality” Acquisition. We work with you to lower your cost and exceed your volume goals, but we also focus on the long-term value of newly acquired customers by applying sophisticated artificial intelligence/machine learning lifetime value modeling to pinpoint the right prospects and the right channel to engage them.

“With Data Axle’s average partnership duration of 12 years, we are confident we will prove ourselves and deliver on your acquisition goals.”

Tom Zawacki, Chief Digital Officer

American | New York

Maintain the Purity of Your Data

Utilize our data processing solutions to remove obsolete, inactive, and nonexistent email accounts from your database. This proactive strategy reduces the risk of facing deliverability issues like high bounce rates, blacklisting, and ISP blocks, all of which could lead to significant revenue loss.

78%

increase in activations

19%

lift in new product activations by existing users

30%

increase in revenue from retained customers

Resideo drives 20% growth with new marketing strategy

Residential technology company Resideo wanted to be positioned as the go-to brand for powering the connected home with smart technology. To do so, the team knew they’d need to update their strategy to engage consumers and homeowners using real-time data to develop and optimize their efforts.

Elevate Your Data

Match your audience’s email or physical addresses with demographic and psychographic data to create accurate customer profiles. This enables you to discover new audience segments, improve cross-selling and upselling efforts, and fine-tune your marketing strategies with precision.

“The B2B Allies Insert Media Team has made the transition for my team at RDA a seamless and painless process that has delivered growth in revenue as promised! These are the types of partnerships we look to for our continued growth and success.”

Reader’s Digest North America

Remove Duplication

Consolidate various data sources into a singular, refined dataset that eradicates duplication, lowers marketing expenses, and bolsters the overall impact of your marketing endeavors.
Target reachable records
Assess your data’s completeness and precision through scoring to pinpoint deliverable and engaged records. Optimize your direct marketing allocation towards these records, heightening conversions within your budget.
Enhance your approach
Access comprehensive analytics on the merging process, pinpointing areas for refining data collection and management strategies, thus minimizing inefficiencies

Key uses of DATA PROCESSING:

What is data processing?

Data processing is the transformation of raw data into meaningful and actionable information through various methods, including cleaning, validation, transformation, and analysis.

Why is data processing important?

Data processing is essential for converting raw data into valuable insights that drive informed decision-making. It ensures data accuracy, enhances data quality, and enables businesses to derive meaningful conclusions from their data.

What are the key stages of data processing?

Data processing typically involves stages such as data collection, data cleaning, data transformation, data analysis, and data visualization. These stages collectively help in turning data into actionable insights.

How can data processing benefit my business?

Data processing can improve the quality of your data, leading to more accurate insights. It helps in identifying trends, patterns, and correlations within the data, which can guide strategic business decisions.

What techniques are used in data processing?

Data processing employs techniques like data cleansing, data enrichment, data transformation, data aggregation, and data analysis. These techniques help convert raw data into valuable insights.