How to Improve Retail Marketing Performance with Actionable Data-Driven Insights

Have you jumped on data for your retail business yet? You probably have. But you may also likely overwhelmed by the deluge of data arriving at your doorstep. As data continues to flood in, it’s no wonder that 57% of enterprise decision-makers report being challenged by data silos that prevent a holistic view of the customer. In addition to organizational silos, current analysis doesn't always produce actionable results in real time, and legacy systems don't integrate with new platforms or meet the needs for improved marketing performance.

How well you can use your data directly correlates to customer lifetime value and overall financial success. Plus, it is the key to understanding, analyzing, and solving new challenges. With the right approach and technologies, it is now possible to collect raw data from multiple sources, analyze it using artificial intelligence and machine learning technologies, and gain actionable insights.

Unlock your data’s potential with GCP Smart Analytics Solutions 

Step 1: Bringing together data from multiple sources

The complexity of data collection compounds with each additional data source. Finding a powerful, yet simple method of bringing data together is the first step to a unified platform that provides a single source of truth.

BigQuery, Google’s multi cloud data warehouse, supports data ingestion using batch loading or streaming. It supports data input from Google sources such as Google Ads, Google Play, and YouTube, external sources such as Amazon S3, and also from on-prem data centers. By supporting multiple data sources, all the critical data that impacts your business from CRM, Google Ads to product and sales can be pulled together in one place for analysis.


Step 2: Run analytics at scale and democratise insights with built-in ML Model

Analysis and visualisation enable better data-driven decision-making. BigQuery ML lets you create and execute machine learning models in BigQuery, and increases development speed by eliminating the need to move data. These customised machine learning models can help segment customers and predict the lifetime value and conversion rate of a customer. CloudMile, the Premier Partner of Google Cloud, also provides customised ML models that meet the needs of retail business. 

Customer segmentation is the process of categorising customers into logical groups. This segmentation is important for gaining insights into current customers and helps to inform actions to retain those customers. After all, it’s far more cost-effective to keep existing customers than attract new ones. Segmentation is also important for focusing retention efforts where they will be most valuable. Long-term customers buy more frequently, and usually spend more money than one-time customers, so each group needs a different approach to market to them. 

On the upside, segmentation can reveal unrealized opportunities that could point to possible trends that appeal to certain customers. This helps to keep marketing efforts focused on those most likely to be interested by offers related to those trends. On the other hand, segmentation can also reveal where you are losing customers so you can take preventative action to retain their loyalty. This is especially important in today’s competitive market, where some stats show that 50% of all customers are likely to switch brands after only one bad experience. It pays to gain the insights that help get them to stick around. Segmentation on big data sets is accomplished with machine learning analysis and business intelligence tools.

To visualise the data BigQuery BI engine integrates with business tools like Google Data Studio and popular business intelligence tools like Looker. 

Step 3: Make data-driven decisions with Business Intelligence tools

Looker is a business intelligence software and big data analytics platform that helps you explore, analyse and share real-time business analytics easily. The Retention Analysis Block, for example, provides insight into the factors that influence customer retention and details how well you are retaining each segment and which segments are the most valuable. This ready-to-use solution can unearth valuable insights with just the click of a button, so you can get a 360° view of your customer, stay one step ahead of problems and take action to serve your customers better than ever before based on the insights driven by your data. 


Get better data-driven insights with CloudMile! 

Better data insights are only a click away.  Building a Customer Data Platform with Google has unique advantages including building better digital ad campaigns with Google Marketing Platform and supercharging your consumer & marketing data with Google Cloud Platform. Join other retailers like Home Depot and Pizza Hut who already use Google Cloud to get the most out of their data and turn them into actionable strategies. 

CloudMile is a cloud and AI company that can help your business make the leap to Google Cloud and put its technology to good use for your company’s aims through our technical support and cloud managed service. For more details, please visit our website!

Read more:

The Benefits of adopting a Data-Driven Retail Strategy

How Retailers Get the Most Out of Data with Data Warehouse BigQuery

Why is Working With a Cloud Partner a good idea?

Top 3 benefits of working with a cloud partner. Accelerate you data transformation with CloudMile and Google Cloud!

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