Deliver personalised offers to your customer to attract and engage new and existing customers!
A big challenge for marketing in the retail industry is, matching business with the everlasting changes of customers’ preferences and expectations. To answer this challenge, you need to segment your audiences and target them. Most marketing departments in the retail industry are using RFM analyses (Recency, Frequency, and Monetary value) to segment their markets. This method is not relevant enough due to the customers’’ hidden patterns (too deep and complex). The RFM analyses are showing their limits and the resulting segmentations show a lot of mistakes and inaccuracies. These mistakes and inaccuracies will affect the recommendations models (to target the segmented audience) and marketing campaigns will start failing. The main reason for the RFM failure is that it is based on only a little subset of data, which is not capturing some major parts of the customer’s behaviour.
To solve this problem, the retail companies need to build a good recommendation system based on:
- A holistic and automated data collection across the company. The retail sector generates and collects huge amounts of highly valuable data. They need to collect all traversal and available data, from all internal and external sources. The companies need to leverage all the value of this information with adapted data architectures and processes.
- Knowledge sharing. They need to share the new established segmentation insights with decision makers in a standard and managed way.
How can Digazu help the retailers marketing departments:
With Digazu’s end-to-end data science platform the companies can ingest scattered data from all internal and external sources. The platform stores and makes the necessary data available to the marketing department in a standardized and fully manageable way. The platform also allows business analysts to connect the needed applications to heterogeneous data sources and receive the needed data insights in real time. Data scientists design, train, and test the data models to build accurate segmentations to establish recommendation models about the needs and wants of their customers, to create effective and reliable marketing decisions and campaigns.
Starting a holistic data-driven management creates marketing opportunities to develop and measure multiple “what-if scenarios” for the various customers’ segments. It allows the marketing department to undertake accurate and reliable decisions to achieve hyper-targeted marketing campaigns (for example optimising the pricing and offers, cost-effective ordering and shipping processes, or store layout optimisation). Digazu helps your organisation leverage the maximum value of each data and data-driven process to build custom-made “customer experiences”.