29 Jan Top 7 advantages of applying predictive analysis to your sales strategy
Top 7 advantages of applying predictive analysis to your sales strategy
KPIs for a digital marketing strategy (Photography from Freepik)
2020 has been categorized as the year of Artificial Intelligence. Within the sales industry, Machine Learning, Artificial Intelligence and predictive analysis have focused on increasing sales rates.
In previous years we have perceived considerable improvements in digital transformation within sales teams. However, 2020 will be the year in which the use of Artificial Intelligence tools will entail a difference in personalizing sales communications for leads and clients.
AI and predictive analysis tactics have a focus on studying a high volume of data to detect trends and, therefore, to guide sales strategies.
Data vs. Data Science
When we started using data to comprehend consumers behaviour, several milestones were taken into account to establish their level of interest in specific products or services.
These were models strong in data but fragile in everything related to data analysis with AI.
These predictive analysis were just able to foresee prospect intentions once they have made their way into the sales funnel.
With Data Science we are able to understand and analyse a buyer journey comprised by numerous sales stages and with a vast quantity of buyer intent signals.
Due to the last trends in Machine Learning and natural language processing, now we are able to identify buyer intent signals that, in the past, were impossible to detect.
Top 7 advantages of predictive analysis applied to sales
Every sales professional should be able to identify the solutions that better adapt to their business necessities, those that work and those that doesn’t.
Predictive analysis helps you to detect those users with a high level of interest in your products or services, those with higher possibilities of converting into sale.
Which are the main benefits related to the use of predictive analysis in a sales strategy?
1. As a result of allocating consumer behavior prediction and those variables that affect sales to automated models, the time spent on manual analysis disappear.
2. By means of identifying those users with a higher purchase probability, it is possible to increase sales and optimize resources. Take into account that you will be able to allocate your greatest efforts to specific audiences with high success rate.
3. Moreover, keeping in mind that this analysis helps to deduce the most relevant variables to favour successful closing sale, it makes possible to adapt the sales process to specific user needs and in each phase of the procedure.
4. Due to the high volume of accessible data, it is possible to define which actions should marketing and sales teams undertake to unleash beneficial results.
5. In addition, on account of trend analysis, predictive analysis helps you to be on the lookout of possible user reactions and define the best way to respond to them.
6. Due to a wide knowledge of user needs and interests, successful product launch is reinforced.
7. It allows you to gain competitive advantage in the market thanks to a growth in visibility in market trends and buyer intent signals.
Predictive analysis, Artificial Intelligence and Machine Learning applied to sales strategies helps us to save time, optimize our efforts and allocate investment to those actions that give us positive results.
Benefits related to their use indicate the strong value they provide, not just to sales teams, but to every department that carry out actions related to customer acquisition and management.