Background

The customer is a retailer of upholstered furniture. Employees regularly receive extensive lists of products: furniture with a description, reference number and price. They need to update the prices of these products in catalogs and stores across different regions. This needs to be done in the web application and in the mainframe. Previously, about 10 employees made all changes manually: they copied data from spreadsheets and published it on websites.

Business Challenge

Automate the updating procedure and save time of company employees for more important tasks.

Solution highlights

The procedure was automated on the EasyRPA platform. Now employees only prepare the initial spreadsheet and upload it to Google Drive folder. The robot monitors the folder every 20-30 minutes. When it extracts the data, it navigates the web applications and the mainframe and inserts the new prices in the right places. At the end, the robot submits a report to the manager with the results.

Project results

Now the solution is being prepared for putting into commercial operation.

Background

Manufacturers, distributors and retailers sell the same product groups on the same shelves. Market actors need timely and reliable information about the actions of competitors and their own situation against their background. Assessment is performed manually by merchandisers, sales representatives, supervisors and marketers. This process involves a lot of manual labor and is affected by human factor. Marketers do not have time to process all the photos and reports. As a result, decisions are made based on incomplete data.

Business Challenge

The Customer desires to monitor the performance of merchandisers and analyze shelf display information.

Solution

The goods are laid out at the store by store employees or merchandisers. They take photos of product display (realograms) and send them for verification. The IBA Group team obtained several thousand of these photos. Each of them was checked manually, and as a result, almost 100,000 items were marked.

In the course of work, the team faced challenges that needed to be addressed:

• select for analysis only those photos that contain equipment with goods;
• determine the type of equipment correctly;
• subdivide similar products within one category (for example, bottles of water of different sizes);
• process photos of poor quality: light-struck, cropped and with other defects;
• develop a separate process for the introduction of new products;
• come up with a way to merge several photos of long shelves into one using a neural network.

Our experts coped with all the difficulties and developed a SaaS solution to assess photos of realograms:

1. Merchandisers and supervisors upload photos of stock keeping units (SKUs) on the shelves.
2. Photos are uploaded to the IBA Group data center instead of the company’s local server.
3. AI module Plano Checker analyzes the photo, evaluates its quality, searches for SKUs and classifies them according to predetermined scenario. If necessary, several photos are merged into one.
4. Plano Checker module saves reports on the server.
5. Users may access the reports and analytics through a web browser immediately after uploading a photo.

Outcome

Goods Checker shows which goods are in their place on the shelves and which need to be rearranged. It helps merchandisers to work more efficiently and earn bonuses.

The system uses computer vision to determine if the photo shows the equipment containing the product, what kind of equipment it is, and also what types of SKUs are placed on it. Recognition accuracy ranges from 90% to 98% depending on the category of products and the quality of photos.

Automation leaves time to analyze the information obtained. The solution allows tracking surges in demand and actions of competitors 24/7. The system processes data and generates analytical reports for the needs of each manager.

Business challenge

Improve the quality of customer analytics and services. Collect additional information from public sources: social media and forums.

Solution

The solution collects data from various external sources. Using semantic and cluster models, it identifies objects of interest. It complements existing dictionaries with business terms, calculates a satisfaction rating based on sentiments in comments and reviews, and visualizes sentiment data. Visualization is based on Qlik Sense, however any BI system can be used.

Result

The solution is applicable to any enterprises and organizations that provide services or sell products to a wide segment of the population, which can be discussed on forums, edicated websites and social media.

Business challenge

The company set an objective to assess the efficiency of budget spending on the advertising of manufactured drugs, and to build an optimal advertising strategy.

Solution

IBA Group experts together with methodologists from the consulting company analyzed the costs of advertising in the media, on TV and radio, outdoor advertising and online promotional campaigns. Five-year data were used to take into account the impact of economic factors and seasonal fluctuation. Specialists created an interpretive forecast model with a seasonal component and identified key parameters that influence brand loyalty.

The results of the study showed that outdoor advertising is greatly overestimated and its efficiency needs to be evaluated more carefully. In addition, advertising a single product in a product line may increase sales of all products in a line – the so-called “halo effect,” when brand visibility due to the main product is extended to cover the entire line.

Result

Marketers obtained new tools: a dashboard for comparative analysis of the sales level and advertising efficiency in various channels, and a calculator for the optimal allocation of budgets for the forecast period. They were used to identify budget limits, above which there’s no point to invest in promotion, because the efficiency of advertising campaigns decreases sharply and does not lead to expected sales.

Financiers and budget owners use accurate data to plan investments in each advertising channel for various estimated levels of advertising budgets.

Business Challenge

Support and internal configuration of Unica-based applications for automating marketing processes, and development of ETL applications to collect data from external systems and transfer them to CRM.

Solution

The IBA Group team includes 20 people. Experts are involved in product configuration; create offer templates, project templates, flowcharts. They also develop database models and all ETL processes, and integrate with CRM systems (Atlas, Gaia, Watson Health).

The customer’s website provides for mandatory sign in for customers seeking advice or downloading promotional materials. All customer information is stored in the database. Data is collected, sorted and sent to external system for verification. If it is an existing client, the system returns the user ID. For new clients it creates new IDs. Subsequently, all marketing campaigns are built based on user IDs.

A marketer can customize flowchart, a business logic that triggers further processes. The system makes a decision on each contact: either to immediately send it to CRM for handling by salesperson, or send e-mail with additional materials about the product of interest for the client.

If a customer wants to run an advertising campaign, it may select the appropriate audience from the database. For example, men over 40 who have recently looked into certain products and currently work in a company with more than 10,000 employees. This audience is used to customize emails or test calls.

Result

The system is optimized to work with the largest number of Unica users in the world. This includes 1200 flowcharts that are simultaneously created by marketers around the world. Round-the-clock system utilization: customer offices are located in India, the USA, Romania, Japan and the Philippines.

Business challenge

Create a robot that will place orders on the websites of suppliers.

Solution

Customer’s specialists downloaded data from SAP on a daily basis. For example, they prepared lists of automotive spare parts to be ordered from suppliers. After that, the operators visited the websites and placed orders. The number of orders is large; several operators were involved in the process. IBA Group team created a robot that automatically visits the sites of suppliers and places orders.

Result

IBA Group completed a pilot project — created and deployed a robot capable of placing orders instead of an operator.

Project Overview

Create an application to support the customer’s sellers and business partners selling support and maintenance services.

Solution

Certified Salesforce developers from IBA Group commenced work under the project in September 2019. They joined a distributed team of 100 people, which includes experts in Salesforce, Java, etc.

The application is built on microservice architecture (REST). To manage support contracts, a new solution for Quote-to-Cash processes has been created. The system will be integrated with CRM and ERP platforms.

If the system identifies that the support contract will expire in the near future, then it automatically creates new sales opportunity. A separate customer structure – Territory Alignment – is responsible for the distribution of opportunity between sales specialists. When a sales specialist receives a notification, he/she can proceed to upsale in a timely manner – extend the contract or transfer it to another manager.

Project Results

Now the project is at the MVP stage. The customer can already try the main functionality of the solution, which will be improved in future releases.

Business challenge

Deploy a new CRM for developing an IT company’s business in the area of sales of SaaS products. For this purpose, it is necessary to adapt CRM to the customer’s business processes, and perform several integrations: transfer data from several different systems into one.

SOLUTIONS HIGHLIGHTS

Certified developers and administrators from IBA Group joined the distributed Salesforce team in January 2018. The team consists of 200 people from several countries, including developers, configurators, business analysts, and test automation specialists. 13 of them are IBA Group employees.

The application consists of two parts: CRM – Salesforce Sales Cloud and Quote-to-Cash. At one of the stages of the CRM system, a valid lead is registered and transformed into an opportunity. At the final stage, the Quote-to-Cash process starts: configuration -> quote -> proposal -> contract -> invoice—> ordering -> billing -> provisioning.

The opportunity has various attributes: product, point of sale, customer language, etc. Based on these attributes, the system generates a list of recommended content for sales specialists: selects presentations, white papers and other materials. The application may be integrated with the customer repository to avoid copying of all documents into Salesforce.

In their work, administrators and developers from IBA Group used middleware – the Tray.io platform. Its advantage is that it facilitates integration of Salesforce with many databases and services due to the large number of connectors and ETL (Javascript). The application has been working since April 2018 and is now gradually switching to the support phase.

Result

A convenient solution for sellers and business partners of the customer who sell SaaS products. Integration with the customer’s marketing platform: its leads are transferred to an external system. Over 2 years, revenue from orders that were switched to quotations in this system increased 10 times.

Challenge

The customer hired IBA Group to test, if the RPA (Robotic Process Automation) and AI (Artificial Intelligence) technologies for which they bought a license suit their needs.

The bank receives a daily list of transactions on currency exchange. Bank employees have to compare the list with data in the internal banking system. Data come in exls, pdf, html, and plain text formats. In cases of data error, clarification of information routed to employee (Human Task)

SOLUTIONS HIGHLIGHTS

Classify input data, automate data extraction (cognitive automation with training model based on 1,500 documents), compare input data with data in the banking system (RPA task), and send messages on process results (bot task).

IBA and the customer worked together on the Proof-of-Concept, implementing the most typical business processes. The project duration was three months. Of these, IBA Group spent one month at the customer’s premises and two months working from an offshore location.

Project Results

1. Automation rate for extraction: 78%
2. Average accuracy: 94%
3. Reduction in manual effort per transaction: 63% (1 m 50 sec vs. 5 min)
4. For Excel: accuracy 100%, automation rate 100%,

As the proof-of-concept yielded positive results, the project was put into production.