Obtain the path to gain & path to loss to get a better picture of the market status.
- Optimize price structure
- Discover the most profitable customer segments(dynamic clustering with the fragmented customer base)
- Improve the efficiency of the supply chain
- Reduce cost
- Identify the causes of the low-profit-margin
- Turn inventory analytics into sales
- Measure the impact of CSR(Corporate Social Responsibility) to Increase profit
- Analyse purchasing decisions, discover the key intuitions behind the buying behaviours
Revenue is often considered more vital than profits when assessing the growth of a business. Revenue is like a show that the audiences watch from the gallery while there is a lot going on behind the scene. There is tremendous number of factors affecting the revenue of a business and there are many hidden factors that are waiting to be found from the sales data.
Enhencer can help you to see behind the curtain and to fully understand what matters most when it comes to revenue maximization.
- Obtain the “Path to Gain” & “Path to Loss” to get a better picture of the market status of the business.
- With the machine learning algorithms obtain the factors driving the sales figures up or down.
- Unlike typical methods, Enhencer helps you to obtain such powerful result in a matter of minutes.
Selling to an existing customer is often more efficient than it is to acquire a new customer. The most profound business strategy to improve profit figures is to up-sell and cross-sell. In order to successfully implement cross-sell and up-sell strategies business needs to focus its efforts on meeting the customer’s needs, rather than simply gushing out more lackluster products and services from its product line-up. This requires extensive analysis of market research data to understand the market for such products.
Bring down the intricacy of market research data and learn how to implement the cross-sell and up-sell strategies.
- Target the right customers for the cross-sell and up-sell strategies using the dynamic & vigorous segmentation techniques that Enhencer offers.
- Obtain products suitable for cross-selling and up-selling based on their features and their demand in the market using the machine learning algorithm.
- With Enhencer, dive deeper to extract such compelling results and implement strong marketing strategies for confidently.
The term shelf fullness is neglected more often than it deserves. It might not be most relatable for all the industries but it’s very important for Fast-moving consumer goods (FMCG industries) Even in this industry, it is being neglected wildly due to its immensely convoluted data structure. Properly analyzing these data can result in invaluable information which can lead to better sales strategies.
With Enhencer, dig out the reason why and where the shelves are left empty, or even displacement of the products in terms of product placements.
- Using the dynamic segmentation, find specific regions/stores where the shelves for the specific products are empty/full.
- Find the reasons why specific shelves for specific products are empty/full.
- Dive deeper into the data with the Data Mining power of Enhencer to obtain such insights with high precision.