P R E D I C T I N G 3 P D A T
Y O U R L O C A T I O N S
2024 Calculating Carry Out: Predicting 3PD at Your Locations
Even after the attribution challenge is
solved, forecasting the impact of 3PD
at potential stores or estimating the
ROI of 3PD-related remodels (like
splitting a kitchen or reconfiguring
counter space) is still a complex
undertaking. Your model's accuracy
will depend on your ability to create
true comparisons between locations,
and while many site selection
solutions can separate 3PD sales,
reliably forecasting it is where they
fall short.
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1. The data restaurants collect isn't
always as reliable as their models
may assume
2. Their models tend to use a single
algorithm for all of their customers,
and can't account for the unique
combinations of variables that
impact each business
The problem is twofold:
staff rings them up differently when
the store is busy. Before broadly
applying it to your model, it's crucial
that you investigate anomalies and
analyze collection methods to test its
reliability.
This is why Tango doesn't simply
input data and perform calculations—
our team of experts works with yours
to vet your data and determine its
quality and relevance to your site
models. Then we work through a
series of up to 30 questions relating
to the characteristics of your
individual stores and the trade areas
they operate in, identifying the
variables that most impact store
performance. Rather than relying on
a single algorithm that may not
account for them all or weigh them
correctly, we layer on algorithms with
machine learning to identify the
combination that most reliably
predicts performance.
Suppose a restaurant chain uses a
more informal process for attributing
sales to 3PD, and it isn't consistently
applied. Or some individual locations
underreport 3PD sales because the
Learn more about how Tango intelligently
combines your data with our suite of data
partners in the eBook, 7 Ways to Use Your
Proprietary Data in Site Selection.
