Grow, Engage, Retain.
Today Marketers compete on their ability to understand their customers and take data-driven actions to drive sales. Emcien not only helps sales and marketing teams to understand their data, but gives them the ability to turn that raw sales and customer data into data-guided actions.
How do you find prospects that look more like your current customers?
Instead of grinding their way through a list of companies that might be good targets, your sales teams could be making targeted calls based on data-driven qualifiers.
Your customers share distinct traits that make them perfect examples of your target market. EmcienPatterns automatically identifies these unique patterns and the EmcienPredict module then uses them to identify prospects that most closely match these patterns.
Find Customer Traits:
There’s no better indicator of a good prospect than similarity to your current customers.
First your CRM and customer data is scanned for predictive capacity with the Emcien pre-analysis tool, EmcienScan. Scanning the data first identifies which data points in your data are predictive of deals won. EmcienPatterns then analyzes your predictive CRM data to identify what characteristics most closely align with your customers. This is a more detailed analysis that goes down to the individual item level to reveal what predicts a completed sale.
The EmcienPatterns analysis will identify and rank each of these patterns to show you precisely what your data can tell you about your customers. There could be ten rules or thousands, but the EmcienPatterns analysis is the only way to quickly identify every predictor.
Match traits to new prospects:
Once the analysis has identified the patterns that are predictive of your company’s customers, the EmcienPredict module can apply those patterns to third party data sources like data.com or Dun and Bradstreet to identify and prioritize new prospects. Each company is given a predictive score to gauge its potential along with the predictive patterns that contributed to its score.
Prioritize your Sales efforts:
With the predictive prospecting of your third party data, your sales team will have a list of prospects that are most closely aligned with your past successes, prioritized by their likelihood to close, and matched with the reasons that each is predicted to be successful. Your sales team will know not just who to call, but why. With data driven prospecting you’ll be more successful, more efficient, and more profitable.
What do you know about your customers?
Emcien automatically identifies the natural segments of your audience to match characteristics with the likelihood each user will click.
With the explosion of digital marketing, companies look for audience segments to target based on their likelihood to buy, and they want to target them in the right place and at the right price. With Emcien, each user is put in a precise segment to match them with the most appropriate action. Marketers know the segments and can create targeted content to capture a wider audience. Each segment is served the right message to cause them to act.
Engage More Customers:
Enticing a customer to buy, click, or follow means matching what you know about your customers with the right content. Emcien’s analytics solution allows you to summarize the different groupings in your customer data to understand the different micro-segments and predict the ad, offer, or message that will entice each group to act.
Define your Customer segments:
Emcien analyzes your data to determine the natural groups that make up your customer segments. You’ll see all of the different kinds of audience members arranged by their predicted outcome. Customers most likely to buy item A would make up group one, those likely to buy item B would be in group 2, etc. Emcien takes all of the different factors that make up the groups and turns them into predictive rules.
Refine your message:
Now that you know the natural makeup of your audience it becomes easier to define what will appeal to each of those groups. These rules help you define the audience and create targeted messaging to guide your audience to action.
Predict on new users:
Those predictive rules are then used to describe your new audience members. If a prospect shares many of the same data points as Group one, she will be matched with Group one and given a prediction of how likely she is to buy item A. For each user you will know how likely he is to buy and what he is most likely to buy, showing you what prompt is most likely to be effective.
Better messaging, more highly targeted, reaching the people they were meant for. You improve your overall response rates by making sure that ads are matched to the groups they were designed for, giving you improved overall response rate.
What makes your customers churn? How can you predict and prevent it?
Preventing customer churn represents a major opportunity for cost reduction. Identifying who is likely to churn, why, and how to intervene whenever possible will enable cost savings and revenue increases for any company that relies on a subscription model or long-term relationships with repeat customers.
Automated Churn Prediction:
Customers don’t always churn because of a single, obvious factor but often a combination of factors. Analysts use EmcienPatterns to identify the patterns that indicate churn and match them to your current customers. EmcienPredict will show you who will churn, how likely each is to churn, and why.
What Predicts Churn:
Getting in front of customer churn means knowing why your customers leave.
Understanding what leads your customers to end their relationship begins with knowing what data is most relevant to the outcome. Direct EmcienScan to your data source and it will identify the categories that predict your outcome. The data is then analyzed with EmcienPatterns. This analysis will identify all of the factors that indicate a customer is likely to churn, down to the item level, even revealing the co-occurring factors that lead to churn.
Predicting on Current Customers:
With the predictive churn patterns identified in the analysis, they can now be applied by EmcienPredict to make individual predictions on each customer. The result is a list of customers ranked by their likelihood of churning, along with the reasons for each prediction. These predictions make it easy to target customers proactively, addressing the specific issues that indicate churn for each customer.
Targeting Customers’ Issues:
The churn prediction gives several opportunities for companies to get in front of churning customers, offer targeted solutions, and prevent them from leaving.
- The information can be routed directly to a CRM for sales and customer service to reach out to customers.
- Discounts, advertisements, and additional benefits can be triggered automatically to improve customer experience.
- Make more extensive changes to your offering to maximize revenues across your entire customer base.
Event Predictions, Network Data, IoT
Telecom customers use Emcien across their organization to solve complex problems, manage enormous data streams, and in many cases completely automate costly networking challenges. Our clients are transforming their industries through unique solutions built with Emcien software at their core.
How do you make predictions on streaming machine-generated data?
Querying test data for predictive relationships is a slow, plodding process. The Emcien approach uses automation to extract predictive patterns and make predictions on new data, even predicting on streaming data in real time.
Real-time Streaming Predictions:
Making predictions on streaming data requires two distinct capabilities, both knowing the predictive patterns and then being able to apply those predictions to new data as it streams by. Emcien’s pattern detection and prediction modules combine to identify these patterns and create predictions on new data as it is created.
Discover patterns in machine data:
The Emcien pre-analysis tool, EmcienScan, is used first to identify the most predictive data.
Emcien analyzes this machine data and will automatically identify the common and repetitive data as noise, isolating the remaining valuable patterns. With only these relevant patterns remaining, the software creates a ranked list of all of the patterns that can be used as rules to predict your outcome.
Rapid, accurate predictions at any speed:
The EmcienPredict module is a lightweight application designed to scale predictions to the needs of Enterprise and IoT. For a traditional data science implementation these predictions can be made at a single location for making prescriptive recommendations for the organization. Already your organization will be miles ahead of the traditional approach of sampling and querying for some understanding of the data.
Prescriptive analytics, automated:
But the industrial Internet and enterprise data science are not limited to the data lab. EmcienPredict modules can be implemented at the data source, making predictions on streaming data on the device itself for distributed, predictive analytics.
How can you know what’s really on your network?
Emcien’s automated analysis solution eliminates the noise from network data to isolate only the data you need to know about. Collect, clean, and act on only the data you need. Track the activity on your network and act to prevent service interruptions, attacks, and other unwanted activity.
Preventing Network Attacks:
Knowing the patterns of traffic on your network is crucial to understanding how you can protect the network from real-time attacks and make strategic changes. Emcien allows you to discover and predict unwanted activity in your network data and act to change the outcome.
Discover patterns of attack:
Knowing the patterns that predict an attack will make you better prepared to intervene and prevent it.
EmcienScan is the data exploration tool, telling you which parts of your data are predictive, giving you an early idea of what can be done with the data and how viable those predictions will be. EmcienPatterns will then perform the complete analysis. This analysis will reveal patterns of all of your network traffic data, including the precise patterns for high priority network attacks. These patterns will allow us to quickly determine what kinds of network traffic are likely to be network attacks, and more specifically what kind of network attacks.
In the hands of the network administrator this predictive data helps in planning network security measures to prevent the most common and costly attacks. With the predictive module, EmcienScan, the network can be monitored constantly to identify threatening traffic as it occurs.
Prescriptive analytics in real time:
With the patterns that predict network attack identified through analysis, those predictive rules are then applied to new network data in real time. The EmcienPredict module will apply those predictions to network traffic, identifying potentially threatening traffic in real time. These predictions can be used to trigger warnings, or can even activate prescriptive actions to thwart the attack.
Instantly identify value in data.
The scale of data today makes it overwhelming to even begin looking for value in data. EmcienScan can quickly scan data for the relationships they contain, showing exactly what data to store and analyze and what data is simply noise.
Smarter Data Management:
Even with the commoditization of hardware and distributed computing, analysts working with truly large, streaming data don’t always know what data is worth keeping. EmcienScan will quickly score the relevance and predictability of your data, giving analysts a quick look into the value of the data so that intelligent decisions can be made about costs and benefits in storage.
Know the value:
EmcienScan tells you where the value is in your data in a matter of minutes. It will score each variable for its ability to predict your outcome and identify how these predictive scores identify natural groupings in the data, giving you a lay of the land for your data.
Keep what matters:
EmcienScan lets you see what’s important to you without any data cleansing or exploratory analysis. You’ll save time and money by working directly with the relevant data and avoiding the typical struggles of “janitorial” data work.
See a Demo
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