Data Strategy for Customer Development

In the article "Interpretation of Data Strategy" published by the International Institute For Advanced Data Management Study, the essential concepts and overall process of data strategy are concisely explained, outlining the theoretical foundations,macro steps, and overall value of data strategy.

A data strategy refers to a set of strategies and actions centered around data that are formulated and executed to propel anorganization's digital transformation and optimization, thereby achieving decision-making and development driven by data. It serves as a guiding principle for enterprises and other institutions in their pursuit of digital transformation.

The data strategy should adhere to a user-centric approach within its ecosystem, be propelled by credible data, and aim at sustainable development as its objective.

For more comprehensive details, please refer back to the article titled "Interpretation of Data Strategy."

Building upon this foundation, the High Court for Data will, from the perspective of how consulting firms initiate data strategy services, gradually dissect and explain the specific implementation actions of each step. This article particularly delves into the detailed steps involved in customer development.

The customer development process encompasses four core stages along with a critical supporting element. The four main stages are as follows:

Throughout the execution of customer development measures, there is a constant emphasis on the involvement of a safeguard, which is ensuring top-notch Customer Service, thus enhancing the customer experience and reinforcing the recognition of the company's capabilities.

After completing the relevant sections of the 'Consulting Engagement Form,' the consulting firm should invite the client company to fill out a scoring questionnaire based on a unified standard system for digitalization indicators. Using the responsesto the questionnaire, combined with their existing knowledge base and experience, the consulting firm can assess the client's digital maturity level—specifically, whether the current state of the business is capable of supporting the transition from traditional operations to data-driven services. If the digitalization level falls below Unit-Level L2, such companies have room for improvement in their data business transformation and may not currently be suitable collaboration partners. For clients rated atProcess-Level L3 or Network-Level L4 and above (with priority decreasing from L5 downwards), in-person visits and interview schedules will be prioritized to explore the potential for establishing a successful partnership.

The scoring questionnaire for the digital component within the six-in-one standard system effectively meets the initial requirements for researching a client's digitalization status. This indicator system was jointly developed by consulting firm Youshu Consulting and a team from Zhongshan University, aligns with national policy demands, and holds high authoritative status.

If a client company's digitalization level exceeds the initial Unit-Level L2, such a client is deemed capable of supporting a transition to data-driven services. Subsequently, the consulting firm internally conducts a rough preliminary assessment of the client's development potential.

The assessment of development potential includes analysis of the industry the enterprise operates in (potentially utilizing the SCP model) and an evaluation of the enterprise's own prospects (potentially employing the SWOT model). The results of thisanalysis serve as the primary decision-making basis for selecting clients and determining fee structures. If a client demonstrates a high development potential, they can be given higher priority, with less stringent constraints applied; in such cases, lighter fee structures may be considered, while also emphasizing face-to-face visits to build amicable relationships and increase the likelihood of cooperation. Conversely, if the enterprise's development potential is less promising, the consulting company will impose stricter conditions on the project, potentially reducing the frequency of interviews and visits to some extent.

Throughout the entire customer development phase, the consulting company must consistently provide customer service, including basic consultation product presentations and timely responses to customer inquiries.

① Basic Consultation Product Presentations: These can be showcased through PowerPoint presentations, encompassing information about the consulting company, its service philosophy, scope of services, expert team, and so forth. This helps customers quickly understand the company's positioning and relevant project experience, thereby increasing the level of trust and the likelihood of signing contracts.

② Timely Response to Customer Queries: Currently, consulting companies primarily rely on project service teams to answer questions manually. However, in the future, they can establish a database of frequently asked consultation questions to enable AI-powered Q&A, reducing time and effort spent on responding.

Customer service conveys corporate values and brand worth, builds trust with customers, and provides personalized services, thereby fostering a positive reputation and attracting more clients.

Data strategy is both a research endeavor and an application practice. The High Court for Data believes that developing implementation templates for data strategy projects from the perspective of consulting firms not only serves as a reference for these firms to roll out their services but also significantly contributes to driving digital transformation efforts across various industries.

This article has introduced the processes and significance of customer development, offering insights that consulting companies can draw upon to refine their business practices. Moving forward, the High Court for Data will continue to delve deeper into the related aspects of data strategy. We encourage ongoing attention and discussion.