Sandeep Bhargava highlights the importance and benefits of developing AI in conducting an effective customer experience and professional business strategy.
In the modern world, every customer belongs to a unique marketing segment. Advances in digital transformation and data modernization enable retailers to target consumers down to the “segments of one” level and, as a result, achieve greater success.
Traditionally, retailers have adopted mass demographic-based segmentation. But retailers embracing the future are using data analytics for micro-segmentation to deliver personalized offers and targeted communications.
According to McKinsey, companies that excel at customer intimacy generate 40 per cent more revenue, with real-time personalization delivering a return on investment (ROI) of five to eight times marketing spend and increasing sales by 10%. Those are big numbers for any retailer, but achieving them is easier said than done, especially with inaccurate data locked in multiple silos.
As artificial intelligence-based analytics continues to evolve, businesses can leverage significant amounts of data to create customer microsegments easily, which can harness specific details to segment at an even deeper level to deliver unparalleled personalization. Yet, despite all of today’s modernization capabilities, many businesses are still struggling to extract value from their data.
Rackspace Technology® AI/ML Annual Research Report 2022 found that only 45 per cent of Singapore IT leaders understand how Artificial Intelligence (AI) and machine learning boost marketing effectiveness. However, many leaders still recognize the value of AI and machine learning for creating a more personalized customer experience — with 77 per cent of respondents agreeing that it has helped them with customer relationship management.
An example of local organizations benefitting from AI personalization includes Southeast Asia’s leading e-commerce marketplace Shopee. Leveraging data and AI, the platform identifies patterns and insights from browsing and purchase data while enabling brands to deliver distinct shopping experiences.
The first two steps in boosting the power of your marketing programs are understanding how to extract value from your data and how to use AI to overcome the challenges presented by micro-segmentation.
Integrate Your Data
Effective micro-segmentation requires accurate and complete data. One problem in achieving this goal is that retailers often have several brands, each holding siloed and disparate data.
Micro-segmentation depends on a deep understanding of your customers. But you cannot get that with gaps in your data. Any flaws will inhibit your goal of delivering micro-segmented, personalized experiences to your customers.
The key to overcoming this problem is to consolidate all internal and external sources into one customer platform. Then you need to make the data easily accessible to your marketers in a simple-to-digest format.
Benefits of Deploying AI
There are clear challenges for retailers in configuring their data for personalization. However, for most companies the solution is within reach and simply requires modernizing their data storage. How can AI help you to micro-segment your target audiences? By giving you the ability to achieve these goals:
- Share data between all areas of your business, so everyone has access to greater insights.
- Deploy visual data transformation to make it easy for everyone to understand data without code-wrangling
- Deliver highly personalized customer experiences based on deep data
- Recommend products based on data such as consumer purchasing history, engagement on social media and current trends
- Provide product recommendations that use contextual communication; for example, “It’s a cold day outside: try our limited-edition mint flavor hot chocolate.”
Personalization is the future of retail. But to get it right retailers need fast and easy access to accurate data. Data transformation and AI are leading the way. Thanks to data modernization and the ability to access insights from large amounts of data quickly, marketers can provide highly personalized messages to consumers that potentially deliver a significant increase in sales.
Data-driven personalization helps organizations optimize resources, like time and money, and instead divert them towards expanding intelligent applications and services. Cloud computing is an asset to decision-makers because it empowers organizations to harness data granularity, leaving out the ifs and buts to drive businesses down the path toward the front- and back-end efficiency.
