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配送保護:消費者の信頼を築き、新たな収益源を開拓 さらに詳しく

約束

インテリジェントでパーソナライズされた配送見積もりによる電力変換

AIを活用した配達予定日をチェックアウト時に提供することで、購入の信頼度を高め、収益を上げることができます。

インテリジェントでパーソナライズされた配送見積もりによる電力変換

コンバージョンを促進するインテリジェントで高度に設定可能な納期

米国の消費者の 45% 以上が、配送に関する懸念が解決されなければオンライン取引をやめると答えています。Narvar Promiseは、小売店がこれらの懸念事項を解決できるようになり、目に見えるビジネス成果を上げながら消費者体験を向上させています。さらに、Narvar には ROI パフォーマンスダッシュボードが用意されており、結果をリアルタイムで分析できます。

+95%

Narvar Networkの何十億ものデータポイントでトレーニングされた複数の機械学習 (ML) モデルを活用した正確な納品日各モデルは継続的にデータから学習します。

60%

注文時に荷物が到着する正確な日付を教えてくれる小売業者を選ぶ傾向が高い買い物客の割合。

45%

配送に関する懸念が解決されない場合、オンライン取引を中止する米国の消費者の割合。

仕組み

納品予定を明確に設定する

Narvar Promiseは高度な機械学習(ML)モデルを採用しているため、購入後の体験を購入前のコンバージョン手段として活用できます。

コンバージョンを最大 4% 向上

商品ページからチェックアウトまで、カスタマージャーニーのあらゆる段階で買い物客の信頼を高め、コンバージョン率を高めます。

AIを活用したインテリジェントな配送見積もりを提供

ビジネス目標に合わせて納期見積もりを最適化

複数の配信オプションを定義し、EDD範囲を設定して、コンバージョンと精度の完璧なバランスを実現します。

ROIをリアルタイムで測定

納期のパフォーマンスや注文コンバージョンへの影響を分析し、目標達成に向けてプロミスを最適化します。

A woman is looking at her phone while sitting on a bench purchasing sneakers with multiple shipment methods from standard to express or priority delivery.
Narvar logo in the center with four data models including origin prediction, fulfillment duration, carrier prediction and transit.
Retailer estimated delivery options showing ability to customize carrier, pricing, and EDD location including checkout, product detail and shopping cart pages.
A woman is shown with a graphic that says "forecasted delivery vs customer demand".

「選択した配送方法に基づいて、別のお客様に異なる(配送予定日)を表示できます。また、顧客が受け取るメールは現地の言語で書かれています。」

ヴェレナ・シュトランク=ヴェンツル

カスタマーエクスペリエンスのグローバル責任者 ON

Frequently asked questions

What is an estimated delivery date and how is it calculated?

An estimated delivery date (EDD) is the predicted day or window within which an order will arrive at the customer’s address. It’s typically calculated using factors like order fulfillment time, carrier transit time, and shipping location. For customers, EDDs provide clarity and trust, helping them decide whether to complete a purchase and plan for the arrival of their order. For retailers, accurate EDDs can increase conversion, reduce cart abandonment, and decrease customer service inquiries. They’re increasingly a competitive differentiator, especially when shown before checkout.

How accurate are estimated delivery dates on e-commerce sites?

Estimated delivery date accuracy varies widely. Accuracy can dip during peak seasons due to weather, carrier backlogs, or inventory issues, but consistent, transparent estimates matter more to customers than speed alone. Retailers using Narvar Promise can hit up to 95% accuracy by combining historical performance data with AI-powered, predictive intelligence that adjusts in real-time to maximize conversion.

Why is the estimated delivery date important for online shoppers?

Estimated delivery dates give shoppers a clear expectation of when their order will arrive, helping them plan purchases and avoid uncertainty. Customers rely on EDDs to plan for gifts, events, and time-sensitive purchases. Accurate EDDs build trust, reduce cart abandonment, and can influence which retailer a customer chooses. Clear timelines also cut down on “Where’s my order?” inquiries, improving the overall shopping experience. In fact, 60% of shoppers are more likely to choose a retailer who can tell them the exact date a package will arrive at the time they order.

How can retailers improve the accuracy of estimated delivery dates?

Retailers can improve estimated delivery date accuracy by leveraging real-time carrier data, using predictive analytics or machine learning to factor in historical performance and seasonal trends, and syncing inventory with fulfillment locations to ship from the closest source. Narvar Promise combines all of these elements to give customers reliable delivery timelines from product page to checkout. Retailers can also adjust cutoff times and update EDDs proactively if delays occur, ensuring customers always have the most accurate, up-to-date information.

What makes Narvar Promise’s estimated delivery dates more accurate than carrier estimates?

Carrier estimates often rely on standard timelines, while Narvar Promise factors in your specific fulfillment data, seasonal trends, and real-world carrier performance for more precise estimated delivery dates.

How does Narvar Promise differ from other intelligent delivery estimate solutions?

Narvar Promise delivers intelligent delivery estimates in real time throughout the shopping journey, customized for each customer’s location, shipping method, and order details, resulting in higher accuracy and stronger customer trust. In addition, Promise leverages machine learning to dynamically display EDDs in the format that is most likely to convert, whether that’s a specific date, a range, or even strategically withholding EDDs in certain scenarios.

How do I communicate estimated delivery dates to customers effectively?

Communicate estimated delivery dates clearly and early — on product pages, in the cart, and at checkout — so customers know what to expect before buying. Reinforce the date in order confirmations, tracking pages, and proactive updates if it changes. Use plain language, highlight deadlines (such as, “Order within 2 hours to get it by Friday”), and provide context or confidence indicators to build trust. Narvar Promise allows you to deliver accurate EDDS through consistent messaging across all customer touchpoints, reducing post-purchase anxiety.

How does Narvar Promise adjust estimated delivery dates when carriers face delays?

Narvar Promise monitors real-time carrier performance and automatically adjusts estimated delivery dates if delays occur. It factors in live transit data, regional disruptions, and historical trends to consistently calculate the most accurate delivery window.

How do intelligent delivery estimates help reduce customer service inquiries?

Intelligent delivery estimates provide highly accurate, real-time arrival dates, reducing uncertainty about when orders will arrive. By setting clear expectations upfront and updating customers proactively if dates change, they minimize “Where’s my order?” inquiries and free up customer service teams to focus on more complex issues.

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