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MissedFits

$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

Categories

Built by MissedFits, Inc.

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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.

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. more
  • 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

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