DATABERG
Retailers have broadly recognized the importance of data to generate compelling sales insights and customer intelligence. Nevertheless, there is still a long way to go until we see retail companies truly leveraging their data. Alteryx and RetailWire performed a recent survey among more than 350 c-level executives from retail companies that brought interesting results. More than 81% of respondents say they are collecting data. But, as a counterpoint, 60% of respondents consider that they are just "getting there" in terms of data, so they still have a lot to do.
Indeed, data has become a competitive advantage in retail and the companies winning on the data are the ones being able to cope with customer expectations. Retailers now can understand customer needs and behavior at a level never imagined if they make the most profit from their data. So data opens an ocean of growth opportunities in retail for those smart retailers that decide to empower it. And to that end, one of the critical steps is expanding the sources of data and exploring new ones.
Sources of data for creating sales insights in retail
The sources from where retailers can gather customer, sales, and operational data had grown during the last decade. From more traditional sources to more innovative ones, all of them are key to make sure that we are collecting the data required to create accurate and complete sales insights.
- POS data. The systems used in the point of sale, also known as POS systems, track all sales transactions, so, in consequence, generate tons of sales data from where we can understand patterns, trends, and deviations.
- Ecommerce transactional data. Online sales data, joint with online customer behavior data, is continually stored in logs and events in our website backend systems. But if we want to gather data flowing through our API or XML connections, then we would need to put innovative technology in place to collect these ephemeral network transit data that can hide precious information related to searches, inventory requests, non-submitted fields, etc.
- In-store sensor data. Now almost all retailers are equipped with Wi-Fi technologies and the big ones even with sensors and IoT devices. From all of them, we can collect extremely valuable data such as in-store movements of clients, in-store foot traffic, dwell time, customer Wi-Fi usage, etc.
- Supply chain systems. By leveraging data generated in our Supply Chain Systems, we can enjoy predictive analytics for inventory management.
- Social Media. Social media profiles and review sites are a great source of data for retailers, especially for understanding customer expectations and satisfaction level, as well as to track competitors.
How can retailers transform new data into better sales insights
The retailers are fully aware of the diversification and growth of valuable data sources. But for them, it is still challenging to face the collection and analysis of all these new datasets. The increase in terms of volume and variety, and the existence of data silos, difficult retail company to leverage their data. But if a retail company follows these steps, the path towards an effective and empowered data utilization to create new sales insights will be more straightforward:
1. Collecting the right data.
The fact that there are several data sources doesn't mean that we should gather all the data we are generating as a business. At the same time, it won't be a good idea to stick to the data that we are gathering right now and explore what we can do with it. The right approach should identify what we want to do with our data: find the purpose. The purpose will help us to determine what are the datasets we need to leverage. And then, we will be able to explore where the data is generated and what are the technologies we need to gather these data. In other words, our data collection should be driven by our overall data and analytics strategy. But the sad truth is that in many retailers it works the other way around. They define the data and analytics plan based on the information assets they currently have. That leads to incomplete intelligence and missing opportunities.
2. Integrating data.
Once we have the data we need, we must make sure that our data is integrated, cleansed, and enriched. So we have it ready to make the most profit from it in any analytical application. And that's especially important considering the variety of data sources that we can find now. Considering this scenario, it is more than probable that we will find a lot of inconsistencies, duplications, and low-quality data; thus, we need to put the right technologies and processes in place to make sure that we have our data integrated.
3. Applying the best analytics.
This point will deserve an entirely new article. But as a central idea, and with the same approach that we use for data collection, before choosing a tool or concrete application from our data, we need to have a clear purpose or goal. And, then, choose the best way to get the insights and intelligence we need.
4. Share and use insights.
It might seem obvious, but many organizations fail at that point. So they are generating compelling insights, but the relevant information is never used for decision making. Many companies fail in putting the insight in front of the people that should be informed, and that can use the information for making decisions. Sometimes the insight arrives at the people that need it, but not at the right time or in the proper format, so, in consequence, is useless.
What are the benefits of these new sales insights
Exploring and exploiting valuable data to increase our retail and customer intelligence will deliver significant benefits for us. First of all, for us it will be a tremendous competitive advantage; it will help us to define more efficient strategies. In consequence, we will be able to grow our business by increasing sales and lowering costs. Sounds good, right?
Having compelling insights at the right time can help us to cross-sell and drive customer retention. And at the same time, we will be able to manage our portfolio better and predict demand.
Conclusion
Retail is becoming a demanding market with giant threats as big online retailers, which are mastering the art of data and analytics. Thus, being data-drive is not an option anymore. Retailers need to make decisions based on reliable sales insights, not intuition. And to have the sales insights needed, the retail company would need to explore new data sources, ensure the quality and completeness of the data, and implement the proper analytics.
