Retail is one of the most dynamic and data-rich industries where advanced analytics is an essential software feature. It helps retailers to deal with large datasets and competitive pressure, apply appropriate marketing and business development strategies.
What unique opportunities can you get by implementing advanced analytics into your Retail software?
- Price optimization
Smart analytics can provide you with price competition analysis and suggestions on dynamic pricing. Analytical tools will help you to set the optimal price for your products by processing data on demand, pricing history, competitor activity, and stock levels. You can also receive notifications about rapid changes in pricing initiating by competing companies. This way you will react to pricing anomalies faster and protect the financial status of your company.
- Trend forecasting
Real-time data tracking helps you to always be aware of current tendencies in the Retail field. Basing on it you can predict future market trends and adjust your promotion campaigns and assortment accordingly. Analytics is able to collect data from various media sources detecting trends from celebrities and social media influencers that is extremely useful in the fashion and beauty industries. It helps your brand to always stay up-to-date and increase revenue by selling the most popular products.
- Website performance improvement
If you are running online Retail, tracking of your E-Commerce platform KPIs is one of the most valuable measurements for you. Analytical tools allow you to monitor the effectiveness of business development strategies and conversion rates in real-time. One more useful option is the implementation of heat maps for tracking the user journey. This way you can easily identify problem pages on your website and improve them for users’ convenience and purchases increase.
- Better customer targeting
A deeper analysis of your audience allows you to get more customer insights affecting your sales. Smart analytics can collect information about age, gender, location, behavior and preferences. It helps in customer segmentation and improves your marketing strategies and advertising campaigns. For example, data collected with advanced analytics allowed Target to figure out their feminine buyer is pregnant at an early stage and sent her relevant discount coupons throughout pregnancy.
- Customer engagement increase
Staying aware of your customer behavior insights can help you in creating a personalized experience for your audience and increase user engagement. Analytics can collect data on buying patterns and behavior giving you an opportunity for personalization of customer experience. For example, you can create personalized recommendations and user journeys based on specific preferences for building stronger relationships between your brand and your audience.
- Assortment optimization
Modern analytics can track stock levels online and even directly from a connected device. For example, such technology is already used in connected fridges that are able to generate shopping lists with required products using smart analytics and collected data. This approach can be also used for optimizing space and in-store product positions. Another great option is monitoring and analyzing an assortment of your competitors with notification about the latest products appearing in the market.
In most cases, smart analytics implies having an intelligent solution driven by Machine Learning algorithms to provide the most accurate reports and predictions. You can get results in different forms: numbers, widgets, short messages or charts. As a bonus, Machine Learning features will improve multi-channel automation of internal processes and customer experience.
Advanced analytics helps to unlock the power of data and gain competitive advantages for your business from valuable insights and smart predictions. If you want your company to operate in the most effective and profitable way, the Exposit team is always ready to create a relevant analytical Retail solution aligned with your business goals.