Customer data unification is one of the leading techniques to build personalised user experiences. Businesses generate a plethora of data like transactions, customer account information including demographics, marketing touch points and interactions. All this data is collected as sporadic data points spread over different data applications. The main goal is to gather all the data from the different “Silos” and present a consolidated front that can benefit the business in multiple ways.
With a unified view, a company can keep a bird’s eye view on all the interactions made by their customers, including demographics, chats, social media details, and buying preferences and phone calls. All this information comes in handy as it helps the company to view the customer as a sum of opportunities and preferences. Reports have proven an increase in sales ranging from 6 to 10 percent for companies that have applied the customer data unification methods.
Still, there are numerous challenges that the companies have to face in providing data unification like:
1. Large Volume of Data
With the increasing number of data points, the collected customer data is ever increasing. Companies constantly face the challenge of effectively collecting, managing and analysing the humongous data generated. With the increase in data, the cost of storage increases, the software to manage the data increases and so does the IT support cost increases with the increase in a number of issues faced on a daily basis for the data and their corrective actions.
Due to the huge amount of data available out there, effective analytics become a core function to manage and handle the data in the right way. Better software and understanding of the data metrics across the board are the major hurdles in the effective use of the customer data. With time, the software have improved, but so has the cost associated with the high quality of algorithms. For data metric understanding, companies still need to develop proper training programs and upgrade training to keep the complete staff on one page and effectively function as one body.
3. Data Quality
Poor quality of customer data is a very big challenge for companies. Although, the errors are minute, like typos, wrong data input, spelling errors, incorrect data input, wrong field selections and other such errors that make a huge chunk of the data unusable. As a result, regular data clean-up is required. According to a study, poor data quality results in loss of six percent of the annual turnover. Further, poor quality also slows down the marketing performance giving rise to mishits and lost sales.
4. GDPR Compliance
Another major challenge to the unification of customer data is the GDPR compliance. Many companies still face serious concerns over handling third-party data as the information is partially available and the risk of GDPR non-compliance is high.
Nonetheless, the challenges in customer data unification and customer 360 are being overcome with every passing day, thanks to the level of research being put in the field plus improvement in the machine learning. Machine learning provides great help at collecting, managing and analysing the huge amounts of data with minimal human input. In the near future, it is quite probable the level of human requirement in the management of data for sales and marketing would be minimised by the use of AI and ML.
Our team of experts can not only guide you on how to unify your customer’s data but also help you in increasing your sales and target your marketing resources at the right places.
Posted on October 31st, 2018