Datassential assembles large amounts of menu trend data for their clientsu2019 needs. See how Data Ladder helped them match client requests faster than ever before.
Datassential is a leading menu research ﬁrm, with oﬃces in Los Angeles and Chicago. Datassential oﬀers menu trend analysis, new product development, and market sizing solutions for foodservice and retail channel customers.
They oﬀer industry studies in various product categories, such as food items and ingredients (dairy products, meat, poultry, fruits and vegetables, breads and grains, beverages, baked goods, snacks, soups, condiments and sauces, and spices) as well as dishes and menu items that include appetizers and sides, entrees, desserts, and beverages.
The company also provides needs analysis, concept testing, hands-on trials, sales forecasting, and brand evaluation processes to deliver informed recommendations for positioning and enhancing brands.
Servicing the millions of food service and restaurant operators in the United States, Datassential assembles large amounts of menu trend data for their clients’ needs.
From determining the fastest growing burger toppings to pricing trends for buffalo wings, Datassential provides hundreds of reports culled from large amounts of data. Bringing together the specific requests by clients and reconciling that with various menu and restaurant types across the country take a lot of time and resources.
The firm had been using Microsoft Access to organize their data but found they needed a quicker and more efficient way of deduplicating data as well as matching information by specific categories.
DataMatch Enterprise™ provided a cost-effective solution for Datassential. The company was able to run multiple match definitions at a very quick speed and found the usability unparalleled with other software suites on the market.
The best in class deduplication capabilities
Through the deduplication tools on DataMatch Enterprise™, the company was able to match their client requests and needs to their databases quickly and more efficiently.
Reduce labor hours significantly
They were also able to reduce their labor hours significantly, as well as improve accuracy.
Run multiple matches at a very quick speed
Unparalleled usability with other solutions