Poplar partners with Faraday to personalize direct mail marketing
Faraday is pleased to announce a new technology partnership with Poplar, a direct mail platform.
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New Faraday Personas & Insights app for Shopify
"This app is incredible. I used Google Analytics, I used other apps, but the level of customer insights you get from Faraday is a complete game-changer..."
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The weighted scale: Mitigating implicit bias in data science
An algorithm contains the biases of its builder. At Faraday, we have a handful of approaches we use to minimize these effects at each level of our machine learning pipeline.
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Customer data transforms marketing strategies at traditional financial institutions
The hype around customer data right now isn't overblown — it supports smarter strategic decisions and lets marketers deliver more relevant experiences throughout their customers' journeys.
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Klaviyo partners with Faraday to power predictions and personalize marketing
Faraday is able to offer our mutual clients a fully integrated experience with Klaviyo, letting users take predictive and personalized marketing to the next level by enhancing Klaviyo’s Listen, Analyze, and Act features with AI-driven personas and predictions from Faraday.
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3 ways to improve your lead scoring strategy
At Faraday, we employ lead scoring to help brands efficiently reach the best prospects. These are some of the practices we’ve found to be helpful when scoring leads.
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Customer insight fundamentals: Building a framework for access and activation
If you’re going to make an investment in machine learning and seek actionable insights from your customer data, you need to approach the effort strategically.
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Customer insight fundamentals: Understand your customer data to make better predictions
Most data scientists practice some version of what could be called a data survey; the goal is to surface meaningful patterns, gaps, and anomalies with an eye toward prediction.
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Customer insight fundamentals: Data requirements for Customer Insights Reports
The rule of thumb is the more data the better. The more information our models can train off of, or the larger data set to glean insights from will allow for much more meaningful results versus just being based on a random or predetermined set of data.
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Customer retention requires data-driven predictions
To scale revenue and drive profitability, companies need to shift their focus to improving retention rates and increasing the average lifetime value of their customers.
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Four ways to extend your acquisition spend with data science
As the first step of building out a loyal customer base, customer acquisition is a high priority for marketing teams. This article explores four ways you can leverage data science to extend your acquisition spend farther to build a loyal customer base.
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Saylent Engage enhances targeting capabilities with Faraday AI
Combining Faraday’s AI-driven predictions with the strength of Engage’s targeted insights and actions will allow our clients to quickly gain a deeper understanding of key customer segments, increasing customer engagement and institutional growth through relevant communications.
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Consider broader changes in your customer data when adjusting your SEO/SEM tactics
As consumers’ spending habits change, companies will see shifts in their customer base... The ability to quickly identify and act on these big-picture changes is just as important as adapting to changes in the more granular aspects of their marketing strategy.
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Strengthening customer relationships during times of economic uncertainty
During times of economic uncertainty, consumer spending inevitably slows. While most companies feel the direct impact, these changes can present opportunities for brands to strengthen relationships with their customers.
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Takeaways from an evening with DTC founders and execs
Discussing everything from choice subscription platforms to how these professionals got their starts in their industries, there were a few key takeaways we’d love to share.
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