Bluecore, the retail and D2C omnichannel personalization platform, is adding experimentation to its suite of products. Bluecore’s new Experimentation Hub will enable the testing of campaigns against specific audiences like new buyers or re-activated buyers.
One main aim of this solution is to improve engagement and revenue within brands’ existing customer base against a background of rising customer acquisition costs.
Automated results. Experimentation Hub allows the testing of digital strategies to optimize for desired outcomes. Such outcomes might include increased average order value, increases in orders and revenue per customer and higher conversion rates. Experimentation Hub also automates the delivery of test results so that marketers do not need to do manual calculations or measure statistical significance.
“Experimentation is critical for retailers to determine what’s working and what’s not as part of their marketing strategies, but the only way to make decisions that will impact customer behavior and drive growth is by first understanding the signals of shoppers that indicate movement toward retention or churn,” said Dave Lokes, VP of digital strategy at Bluecore in a release.
Why we care. It’s about building an experimentation culture. Certainly, marketers are already running specific tests — when they have the time and opportunity to do so. Tests might range over placement of CTA buttons, effectiveness of pop-ups and various aspects of content performance. Results from what is essentially limited A/B testing applied to the online experience might not deliver an overall picture of what’s working (and not working). Tools that make experimentation easier will encourage more experimentation; and that can only be a good thing.
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**Bluecore Expands Capabilities with New Experimentation Features**
In the rapidly evolving world of eCommerce, personalization and data-driven decision-making have become essential for brands looking to engage customers effectively. Bluecore, a leading retail marketing platform, has long been at the forefront of helping brands harness the power of data to deliver personalized experiences. Recently, Bluecore has taken a significant step forward by expanding its platform with new experimentation features, enabling brands to test, optimize, and refine their marketing strategies more efficiently than ever before.
### What is Bluecore?
Bluecore is a retail marketing platform that leverages artificial intelligence (AI) and machine learning (ML) to help brands create personalized customer experiences across email, eCommerce websites, and paid media channels. The platform is designed to help retailers understand customer behavior, predict future actions, and deliver tailored content that drives engagement and conversions.
Bluecore’s core strength lies in its ability to unify customer data from various sources, including browsing history, purchase behavior, and product catalog information. This data is then used to create highly personalized marketing campaigns that resonate with individual customers, increasing the likelihood of conversion and long-term loyalty.
### The Importance of Experimentation in Marketing
In today’s competitive eCommerce landscape, brands must continuously test and optimize their marketing strategies to stay ahead. Experimentation allows marketers to evaluate different approaches, measure their effectiveness, and make data-driven decisions that improve performance over time. Whether it’s testing different subject lines in email campaigns, experimenting with website layouts, or optimizing product recommendations, experimentation is key to finding what works best for a brand’s unique audience.
However, running experiments can be a complex and time-consuming process, especially when dealing with large amounts of data and multiple marketing channels. This is where Bluecore’s new experimentation features come into play.
### Bluecore’s New Experimentation Features
Bluecore’s new experimentation capabilities are designed to make it easier for brands to test and optimize their marketing strategies across channels. These features provide marketers with the tools they need to run controlled experiments, analyze results, and implement changes based on data-driven insights. Here are some of the key features included in this expansion:
#### 1. **A/B Testing at Scale**
A/B testing is a fundamental method for evaluating the performance of different marketing strategies. Bluecore’s new experimentation features allow brands to run A/B tests at scale across multiple marketing channels, including email, website, and paid media. This enables marketers to test different variations of content, offers, and messaging to determine which approach resonates best with their audience.
For example, a brand could test two different email subject lines to see which one generates a higher open rate, or experiment with different product recommendations on their website to see which ones lead to more conversions. The platform’s AI-driven insights help marketers quickly identify winning strategies and implement them across their campaigns.
#### 2. **Multivariate Testing**
While A/B testing compares two versions of a single variable, multivariate testing allows brands to test multiple variables simultaneously. Bluecore’s new multivariate testing capabilities enable marketers to experiment with different combinations of elements, such as images, copy, and calls-to-action, to determine the most effective combination for driving engagement and conversions.
This feature is particularly useful for brands that want to optimize complex marketing campaigns with multiple moving parts. By testing different combinations of variables, marketers can gain a deeper understanding of how different elements interact and contribute to overall performance.
#### 3. **Real-Time Experimentation**
In today’s fast-paced digital environment, waiting days or weeks for experiment results is no longer practical. Bluecore’s real-time experimentation capabilities allow brands to monitor the performance of their experiments in real-time, making it easier to identify trends and make adjustments on the fly.
For example, if a brand notices that a particular email variation is underperforming during an A/B test, they can quickly pivot to a different approach without waiting for the experiment to conclude. This agility is crucial for brands that need to respond quickly to changing customer behavior and market conditions.
#### 4. **Advanced Segmentation and Targeting**
One of Bluecore’s standout features has always been its ability to segment customers based on their behavior, preferences, and purchase history. With the new experimentation features, brands can now run experiments on specific customer segments, allowing for more targeted and personalized testing.
For instance, a brand could run an A/B test on a segment of high-value customers to determine which type of offer (e.g., free shipping vs. a discount) is more effective at driving repeat purchases. This level of granularity ensures that brands are not only optimizing their overall marketing strategy but also tailoring their approach to different customer segments.
#### 5. **Comprehensive Reporting and Insights**
Bluecore’s new experimentation features come with robust reporting and analytics tools that provide marketers with detailed insights into the performance of their experiments. These reports include key metrics such as conversion rates, click-through rates, and revenue impact, allowing brands to measure the success of their
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