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Stepping up the business model with a Pricing Analytics powered strategy

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Client Location

Asia

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Client Industry

Food and Beverage

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Services Provided

Data strategy and data visualization tool

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Technologies Used

Python, Django Framework, Angular, Pandas, Numpy, Jupyter & AWS

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Allocated Team Size

16+
Engineers

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Project duration

52+ Weeks and ongoing

Client

Client Background

This AI and Machine Learning tool built for the largest chain in the Food and Beverage Industry. They have outlets in over 100 countries serving more than 50 million customers daily with quality food.

Franchise business models decentralized their execution and every region has its own abilities to create menu, quantity and pricing. The central business intelligence team offers recommendations for every franchisee owner about Food menu preferences based on local region’s Interest, pricing policies and quantity. This approach helps franchise owners to analyze business recommendations, assess and act towards running business in a profitable manner.

Requirement

A Pricing Analyzer tool to help the company to identify the pricing strategy, best price of its products, system to analyse the price with competitors and set the accurate price that offers maximum profit while offering sales growth and customer loyalty.

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Problems

Business Challenges

01.

Fixing up the right price for each item is the most critical decision for a Store.

02.

Price Equalizer Tool: If the Price is too high, you lose the Customer and if its too low, you lose the margin

03.

Define Sales price by assessing raw material cost, incremental labor cost and compliance expenses.

04.

Profit margin will be defined based on customer food preferences and intensifying competition.

Tech Architecture:

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Methodologies

Our Process

We at W2S Solutions follow a set of strategies in order to make the business successful and enhance profits. Here are the steps which we follow for our clients:

01

Understanding the playbook

Reviewed the current pricing process and defined rules for recommendations.

02

Adjusting the system

Tailored solution with the pricing engine and recommendations portal to help each Stores.

03

Incorporating solutions

Offer easy onboarding of Store Owners & Operators, combined with an easy to use system in reviewing and uploading the final price to the POS

04

Fusing ML for efficient results

Dynamic Pricing leverages Machine Learning based on the latest Data

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Our Team

Team Structure

A talented team of 15+ professionals who specialized in niche skill sets such as Application Development, Data Analytics and Cloud Deployment services.

As the team is matured and energetic, they are aware of Individual responsibilities and stand together as a team in order to meet the deadline and requirements.

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UI/UX

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Data Analyst

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Cloud Architect

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Quality Analyst

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Mobile App Developers

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Backend Developer

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Projects Manager

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Front End Developer

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Customer Success Manager

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Tech Stack

Tools and Technologies

Results can only be driven by choosing the correct technology stack. As we have great experience in handling such Digital Transformation Solutions, we had handpicked the following tech stack to build a rock-solid application that should be capable of handling big data and should also provide flexibility for easy customization in the future.

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Communication Tools:

  • Slack was used for internal communication within the organization.
  • Google Meet or Zoom Meetings to interact with clients.
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Technologies

  • Backend - Python, Django Framework
  • Frontend UI - Angular
  • Data Analytics - Python, Pandas, Numpy & Jupyter
  • Cloud - AWS
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Project Management Tools

  • JIRA -Task Tracker and Sprint Plans.
  • Github- Version Control.
  • Confluence- Document Management.
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Outcome

Solutions Offered

Result

Business Impact

Predicti

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Predictive Analytics

Leveraged Internal and External Data sources using Advanced Analytics to predict future sales, and continuously update recommendations based on actual sales.

BetterP

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Better Profit Margins

Price Analyzer recommends price which aligns with consumer's willingness to pay and resulted in higher margins through optimized pricing.

Performa

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Performance Tracker

Helps Stores to track the performance of recommendations by providing sales and profit insights

Frequently Asked Questions

What is a Pricing Analyzer Dashboard and how does it function in the food & beverage industry?

A pricing analyzer in the food and beverage industry is a tool or software that helps businesses analyze their pricing strategy and make data-driven decisions about pricing their products. Using a pricing analyzer, businesses can perform price sensitivity analyses, track market trends, and adjust their pricing strategies to stay competitive and maximize profits. 

Some food industry pricing analysis software also incorporates data on customer behaviour and preferences, allowing businesses to identify which products are most popular and adjust their pricing accordingly.

How can beverage pricing analytics help businesses to make better pricing decisions?

A pricing analyzer dashboard can help businesses in the food & beverage industry make better pricing decisions by providing them with real-time, actionable insights into their pricing strategy. Big data intelligence uses these factors to determine what a customer is willing to pay at the optimal price.

What kind of data is required to generate insights on a Pricing strategy in the food & beverage industry?

To generate insights on a Pricing Analyzer in the food & beverage industry, several types of data are required. Here are some examples cost data, sales data, market data, product data, customer data, seasonal and regional data, distribution and logistics data, and promotion and advertising data.

How does pricing analytics in the food & beverage industry differ from pricing analytics tools used in other industries?

A Pricing Analyzer Dashboard in the food & beverage industry may differ from pricing analytics tools used in other industries based on several industry-specific factors. A pricing strategy for a F&B brand is in which a company sets flexible and variable prices on its food and beverage products based on a variety of independent or competing factors such as demand, supply chain, competition, location, time frame, and other market conditions.

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