Artificial intelligence-based sales coach
Pega Sales Automation application uses built-in decisioning capabilities to
provide managers with insights about how sales representatives perform during their 90-day
probation period. During the first 90 days, the adaptive models analyze data about the sales
representatives including their profession, experience, training performance, weekly
pipeline data, and the pipeline delta. The Pega Sales Automation application suggests actions to managers based on the
performance of sales representatives. It also provides suggestions to sales
representatives about how to improve their performance. The artificial intelligence
model predicts the probability to reach the target, for example, reaching a target of
$300,000 in 18 months. You can configure the definition of success ($300,000), T-Zero (3
months), and T-End (18 months). The Recommendation dialog box contains
details about the Recommended Value and
Current Value for the selected category
for the sales representative. The recommendation status becomes
Active and a notification is sent
to the sales representative indicating that a coaching plan has been
assigned. Only the sales manager and the sales representative can see these Pulse
communications—they are not visible to anyone else in the
organization. Pega Sales Automation uses self-learning, adaptive models to generate the
effectiveness scores for each sales representative. This method is based on core Decision
Strategy Manager capabilities. If needed, you can add or remove predictors. The Pega Sales Automation application has the following predictors in
the adaptive model: Pega Sales Automation uses predictors ranging between Pega Sales Automation and Human Resources that are listed in the
PredictEffectiveness model, for example, sales representative
pipeline, delta of pipeline, predictive indices, previous company details, and human
resource statistics. You can configure the outcomes in the adaptive model. After a sales representative
completes the 18-month probation period and achieves the target you specified, the
system sets the outcome to Achieved. If the sales representative fails to achieve the
specified target, or the employment contract is terminated before the 18-month probation
period ends, the system sends failed and terminated outcomes to the models. Coaching actions are evaluated in the SalesManagerCoachingActions
strategy, which calls the CoachingActionsPredictor sub-strategy.
The SalesManagerCoachingActions strategy runs through each
predictor with the representative's propensity and maximum propensity for predictor,
then suggests actions based on that information. The EvaluateEffectiveness strategy is used to train
the PredictEffectiveness model and to predict the
effectiveness score of each sales representative. To train the model and predict the effectiveness score, complete the
following steps: The strategy sets the context for the model and calls the adaptive model.
The system presents the results individually or as a set on the primary
page, which you can configure in the strategy properties in the data
flow. To view the data flow details, perform the following steps:Coaching life cycle and coaching actions
Historical data and adaptive learning
Predictors Human Resources predictors Pipeline current (a number of the opportunities in a
stage) Number of days after joining Delta between two snapshots (a difference between the
current and the previous snapshot) Experience in years Territory Educational qualification Customer Interactions created Business card title Face-to-face (F2F) meetings Job title Other meetings Source of hiring: referred, sourced, agency, direct,
applied Contacts added by sales representative Sub-source for referrals: referred by, referral
functional area Inbound emails Previous company details: company name, size,
revenue Outbound emails Predictive indices, for example: A, B, C, D, PI, A minus
B. Number of leads HR ratings: green, blue, yellow Leads converted to opportunities Other information, for example, number of days for
onboarding, completed courses, grades. Manager Sales coach architecture
Strategies
Data flows
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