DATABERG
During a sales cycle, every touchpoint generates data that reveal customer needs and expectations.
Every click, scroll, tap and pinch can uncover valuable insights into customer behavior. Combined, they create a detailed profile; from this information, companies can build a complex model of a consumer’s digital preferences, desires, and behavior patterns. Filled with actionable information about customer needs and expectations, these data are today’s most valuable business resource. Here, we discuss five necessary steps to obtain and leverage this profitable intelligence.
1. Establish a cross-department data team
To maximize return on a data project, businesses need to align resources. Primarily, they need to ensure a data initiative is correctly staffed. The best approach is often to establish a devoted data team. This working group should include individuals who understand both data science and business. Further to this, the team needs to have an overview of the key challenges that face the organization, including concerns regarding IT, finance, HR, and marketing. Once these challenges are identified, the team can look to data to problem solve.
2. Capture data at a granular level
Not all data are equal – and organizations need to make sure they are collecting the right kind. Therefore, companies should focus on data quality as opposed to quantity, ensuring that their analytics solution targets relevant data. For example, in order to define customer needs and expectations, companies should develop a picture of their digital footprint. This means monitoring every interaction, from mouse movements to conversions. Furthermore, the data team should ensure their project is platform neutral, capturing data across devices. By gathering this information, the data team can gain valuable insights into how customers interact with the business’s digital experience.
3. Implement real-time analytics capabilities
As customers demand an increasingly seamless, responsive service, analytic capabilities should mirror this expectation. By analyzing customer behavior patterns in real time, companies can develop the ability to react to customers’ desires instantaneously. Subsequently, optimized user experiences will result in increased customer satisfaction and conversion rates.
4. Align findings across the business
Every department can benefit from the insights gained from a thorough data project. For instance, the marketing department can identify which content generates the most engagement. Equally, web developers can optimize page design to improve user experience and the IT department can develop a more robust infrastructure in response to detailed crash data. However, the key to ensuring this information is properly distributed lies with the data team. They need to ensure the relevant information is fed back to the rest of the organization in a timely manner.
5. Learn and grow
Like every business initiative, data analysis should be a continuous project. Companies should study how customer needs and expectations change over time. Consequently, they should compare this information to historic analyses to learn from the past. After all, the kind of data provided by experience analytics was never previously available, so it would be counterintuitive to not learn from this new intelligence on an ongoing basis.
Why data is key to learning customer needs and expectations
The key to exceptional customer service lies in empathy and analysis. Through capturing detailed data about customer behavior, businesses can develop complete customer personas. By studying data that reveals how customers interact with the business, the organization can create a user experience that resonates emotionally. As a result, advanced analytics can help business to gain a deeper understanding of their clientele, driving customer loyalty and profit.
