parcelLab Convert

Provide a predictive delivery date that increases conversion rates, reduces consumer uncertainty, and improves customer satisfaction.

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Convert Impact

Less Time Spent on PDP

Convert customers faster on product detail pages with a compelling delivery date.

Increase in Conversions

Assure consumers with a guaranteed delivery date to clarify order arrival time.

Faster Mobile Checkout

Empower customers to make purchase decisions with more confidence.

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Supporting Retailers During the Conversion Journey

The Convert suite helps to reduce delivery uncertainty and increase onsite conversion by providing retailers with a predictive delivery promise date on product detail pages and at checkout. Combined with parcelLab’s Track & Communicate product, Convert can be extended into the post-purchase experience with hyper-relevant updates and personalized content.

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Promise

Powered by our machine-learning algorithm, parcelLab Promise calculates estimated delivery dates based on your warehouse operations and corresponding delivery methods, accounting for ad hoc holiday updates, delivery method changes, multiple carriers, weather closures, and staffing shortages.

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Features

Low Latency API

Out-of-the-box API with flexible request pattern based on data available to the retailer.

ML Algorithm

Random Forest based data model with zip-code level accuracy.

Configuration UI

Easily configure the estimated delivery date from PDP to the checkout page.

Track & Update

Monitor against forecasted dates and communicate with customers accordingly.

Teams That Benefit From Convert:

Ecommerce and Product Teams

Increase sales by providing data-driven predictive delivery dates — decrease cart abandonment rates by lessening delivery uncertainty.

Customer Experience Teams

Improve customer experience by setting data-driven expectations that are consistently met to build consumer trust.

Customer Support Teams

Decrease WISMO inquiries by setting delivery expectations prior to checkout. When coupled with our Track & Communicate product, it reduces the strain on customer support teams.

Logistics Teams

Manage order fulfillment and carrier constraints while delivering a superior customer experience with data-driven lead times and proactive notifications.  

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Customer Impact

Drive urgency and build brand loyalty with transparent, personalized touchpoints

parcelLab’s capability to integrate its solution into HUGO BOSS’s existing infrastructure and offer forecasted delivery dates to their global clients kicked off the long-standing partnership. HUGO BOSS initially wanted to understand where parcels were on their journey to customers. parcelLab not only delivered on that promise, but also overtime integrated personalized emails to their client base with updates on order status, delivery timing and returns.

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BOSE: Our customer focus resulted in an email open rate of 79%

I think that this was one of the main decisions to go with parcelLab because we saw flexibility there, and we really liked the idea, for example, of testing different templates, like doing A/B tests on open rates differ. How does click-rate differ if we put this element up or down, etc?

These tests would internally take a lot longer… but really kudos to the parcelLab team here – they have been super flexible, and everything is done really fast!

Tim Volkmann

Manager – Digital Consumer Direct Europe

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Hessnatur: Targeted timing yields a +365% increase in ratings

When it comes to asking for product reviews, it’s all about the right timing. With parcelLab, we have tailored the shipping communication to the various stages of the process and our request reaches our customers exactly when they are happy to hold their parcel in their hands and are really ready to evaluate and give feedback.

Deborah Kirchner

Online Marketing Manager

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bonprix: 24 message triggers ensure an optimal buying experience

The customer journey is now streamlined and informative. Next, we want to unlock the marketing potential hidden behind the 12 million notifications sent to our customers every year. Thanks to parcelLab, this is possible – it would be a shame to leave this potential untapped

Séverine Toulemonde

Customer Experience Manager

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11teamsports:Customer loyalty pays off with 19% more sales as a result

Our partnership with parcelLab has given us many advantages. Our customers now receive all post-purchase messages directly from us, in our corporate identity and the Order Status page on our site has created some very valuable traffic

Christian Schab

Head of E-Commerce

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Frequently Asked Questions

What’s the core functionality of parcelLab Convert?

parcelLab Convert includes configuration that enables non-technical business users to set up estimated delivery dates on product detail and checkout pages; a machine learning algorithm trained on customer and carrier data attributes that impact timing like holidays, warehouse hours, courier pickup times, staffing shortages, etc.; and a low-latency API ensuring no impact on PDP or checkout loads speeds, responding in less than 8ms.

How is parcelLab different from other vendors?

Most order and transport management systems are primarily designed to manage delivery operations. Our product is designed for non-technical users looking to increase revenue, decrease support costs, and improve customer experience. As a result, parcelLab enables you to provide the right combination of data-driven lead times, proactive consumer notifications, and configuration to easily meet your ever-changing fulfillment landscape.

What’s the effort involved in implementing parcelLab Convert?

An out-of-the-box API allows immediate technical product delivery. The Machine Learning algorithm requires two weeks for retailer-specific training with consumer and carrier data, and configuration of warehouses and delivery methods. In two weeks, you can provide your consumers with delivery date information that grows top-line revenue.

parcelLab’s dedicated and specialist implementation team of data scientists, carrier logistics experts, and project managers helps drive a smooth and efficient timeline that accommodates anticipated data requirement changes, rigorous test plans, and room for necessary user training.