MissedFits

Name: MissedFits Introduction Video
Uploaded: 2024-04-05T02:36:04Z
Duration: 1 min 33 s
Description: Optimize forecasts and drive conversions using shopper data

MissedFits

Develop by Shopify

$1-$149

/ Month

30 Days Free Trial

Optimize forecasts and drive conversions using shopper data

Back-in-stock notifications

Capture missed demand

Trade-out recommendations

About MissedFits

Launched Jul 04, 2023

Built by Shopify

Address

44 Tehama Street, San Francisco, CA, 94105, US

Website Support Portal Privacy policy Tutorial FAQ Document

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Introduction Video

Description

MissedFits monitors out-of-stocks to improve future forecasts and drive conversions of like-styles.

MissedFits captures first-party data of items shoppers wanted to buy but can't due to out-of-stock issues, which allows merchants to determine missed sales opportunities in order to more accurately forecast future assortments to better match demand. MissedFits also uses this data to show shoppers other similar in-stock items using our proprietary recommendation engine to drive sales conversions today.

Capture missed demand of out-of-stock items to improve future assortments
Trade-out recommendations to drive conversions of similar in-stock styles today
Acquire shopper e-mail addresses to deliver back-in-stock notifications

Pros

Captures first-party data of shopper interest in out-of-stock items, allowing for better inventory forecasting
Helps determine missed sales opportunities, aiding merchants in optimizing assortments
Utilizes a proprietary recommendation engine to suggest similar in-stock items, potentially driving immediate sales conversions
Offers trade-out recommendations to convert interest into sales of similar items
Acquires shopper email addresses for back-in-stock notifications, enhancing customer engagement and return visits

Cons

May rely heavily on accurate data capture and processing to ensure effective forecasts and recommendations
Could potentially recommend items that don't meet shopper needs, affecting conversion rates negatively
The recommendation engine might not work effectively if the database of similar items is limited
Requires shopper cooperation to capture email addresses, which might not always be willingly provided
Success depends on the merchant's overall e-commerce strategy and inventory management practices