The Importance of Data Analytics in Telemarketing
The humongous increase in the amount of business data is guiding enterprises to make decisions based on careful data analysis. Data mining and business intelligence have gained interest in recent years in both public and private sectors as they provide a trustworthy and objective basis for making strategic decisions.
While the collection of data is one part of the analytics, using the acquired databases to predict future events is one of the main aspects of business intelligence popularly known as predictive analytics.
Data analytics has slowly transformed B2B outbound telemarketing to the point where it has become a real driver of sales acceleration.
The Side-lining Of Outbound Telemarketing
Till the advent of data analytics, outbound telemarketing was the epitome of yesterday’s telemarketing. But the problem was the data was untargeted, intrusive, and expensive and hence fell out of favor.
To make things more convenient and effective, the gradual adoption of inbound marketing enabled by wider use of the internet by buyers for a better understanding of the need to track the customer journey took center-stage, and eventually, the increasing use of marketing automation tools provided the necessary data with ease.
Most calling programs used a combination of third-party and in-house data. The procured data was of poor quality with limited segmentation and little or no behavioral clues. And, they often reflected responses to past campaigns rather than future plans. The decision making patterns became more complex, telephonic conversation did not necessarily qualify as a lead generation and required multiple calls within the same organization to make progress.
Maintaining The Legacy Of Telemarketing
Outbound telemarketing still continues to survive as it is a proactive medium as long as your budget lasts. The results are instant and give marketers the hold on adding resources and other adjustments in real-time.
The constant pressure for leads has pushed organizations to adopt new and enhanced solutions to accelerate sales with better content. Using predictive analysis, enterprises are managing customer relationships, predicting customer retention and optimizing the efforts of the marketing team along with the application of Machine learning (ML) and artificial intelligence (AI).
The provision of new datasets bundled with other demand generation services including calling is facilitating selective targeting of customers while creating a better experience overall.
Channelling The Entire Data For Telemarketing
The pandemic has fastened the transition of converting hardware infrastructure to software-based processes. Every business is integrating its existing CRM platforms and shifting the on-premise IT infrastructure to the cloud.
Enterprises are able to centralize their sales process or customer care from a cloud-hosted application server including dialer applications creating a single source of data aggregation. Moving to niche solutions like Epicode’s CIP, a unified customer interaction platform that combines the power of communication technology and the ability to collate data from multiple business applications can help marketers with continuous access to actionable data and hence maximize sales conversions.
“The consolidation of various channels of data is a great way to derive meaningful insights, which when combined with well-executed telemarketing campaigns can speed up the revenue cycle and result in a clear competitive advantage for the organization”.
Bottom Line
An effective data analytics model depends on how accurate the data is and hence it decides the outcome of the analysis. The accuracy of data, sets the platform for good business decisions for marketers. By deriving customer data and transaction history from a single unified platform will help marketers deliver the right messages at the right time and in the right place to move potential buyers to the next step in their customer journey which forms the underlying principle of telemarketing strategies.