5 min
Founded over 19 years ago, Denave filled the void in the industry by providing end-to-end sales enablement solutions. They had clear focus on revenue acceleration, optimisation of return on investment and measurable impact by leveraging people, processes and technology. Co-founder and global CEO Snehashish Bhattacharjee spearheads the strategic goals of the company and is instrumental in building the company’s future roadmap.
With technology and innovation as the convergence point, Bhattacharjee is aiming to emerge as the world’s largest sales enablement organisation.
In an interaction with Analytics India Magazine, Bhattacharjee talks about how Denave is disrupting the world of sales using sales process automation, business intelligence, machine learning and analytics to cater companies across the industries globally and also shares his insight on how data analytics is evolving in India:
Analytics India Magazine: How can data and analytics help companies drive better sales? How is Denave enabling companies to accomplish that?
Snehashish Bhattacharjee: Data analytics has a critical role to play in sales in terms of sourcing, checking purchase history and prioritising, identifying probable prospects, and sales process and fulfilment.
Denave, enables the organisations with its tech and analytics practice led services at each of these stages during the entire sales journey. With our solutions, we are changing the industry landscape with the integrity of revenue, proof of execution and ROI orientation that we bring to marketing processes as well as technology solutions.
AIM: Tell us more about Denave’s Intelligent Database Management and other analytics services provided by the company
SB: Denave’s Intelligent Database platform focuses on two primary areas:
- Building a tech-enabled access to organisational level information, that enhances contactability and access to profile information which is relevant to prioritise sales drive focus.
- A suggestion engine (Smart Database Access Platform) which allows identifying the probability of purchase.
- Data Engineering: We consider this a prerequisite to build an effective Data Visualisation engine, leading to impactful sales and marketing analytics.
- Data Visualisation and Dynamic Narratives: We leverage popular platforms in conjunction with our CRM to help provide this as a service.
- Analytics Practice: Here, we presently have built a practice around Retail Analytics which we provide to customers across 14 countries, including India.
- Retail Analytics Practice for one of the world’s largest search engine
- Up to 99.9 percent improvement in data quality
- 2X faster TAT (4 weeks to 2 weeks)
- Standardisation across 14 countries
- Data Visualisation for a technology giant
- Scattered/manual reporting structure
- Lack of process automation
- Lack of integrated view for the overall operations
- Data quality issues
- Excess man-hours and efforts
- 60 percent reduction in TAT
- 360-degree view of business operations
- Higher sales closure analysis based on predictive analytics to identify highest probability verticals
- Incremental revenue opportunity identification
- Geo expansion and SMB penetration based on propensity analysis
- Real-time analysis of agent productivity
- Data-driven higher product affinity analysis
- Effective lead conversion mapped against high performing agents leading to better productivity and higher results
- Resource optimisation and higher productivity analysis through performance mapping
- Data Engineering: Acquiring the data and transforming it into a structured and usable data set for diagnostic and descriptive Analytics.
- Interactive Visualisation: Depicting the information in terms of correlated graphs for better and holistic understanding of data and events.
- Actionable Insights and Dynamic Narratives: A synopsis of the critical information and actionable insights enabling quicker informed decisions.
- Predictive and prescriptive analytics: This stage is to predict the future on the basis of historical information and some external categorical parameters, additionally prescribing the action points on the basis of predictions for future readiness.
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