- Customer Lifecycle Optimization
- Marketing Optimization
- Health & Pharma Analytics
- Automated Analytic Processes
Customer Lifecycle Optimization
Highly Targeted, Highly Optimized
Marketers are constantly seeking ways to efficiently grow their customer base and retain existing customers through direct targeting methods. Predictive models are the starting point, but optimizing marketing efforts also requires making tradeoffs to ensure each incremental dollar is spent as efficiently as possible.
Our optimization solutions leverage the following approaches:
- Customer behavior models. Models that predict response, churn, or other customer behaviors can be built efficiently and accurately using LityxIQ.
- Customer value models. Not all customer are of equal value, neither in the short or long term. The ability to predict lifetime value, and the marketing path to maximize it for each customer, is an important aspect of customer optimization.
- List rental and data overlays. Whether for direct mail, email, shared mail, or other channels, we can provide targeted lists or media as the starting point for optimizing selections. We can also overlay hundreds of data elements to ensure as much information as possible is utilized in models or optimization decisions.
Optimizing Print Channel Acquisition Optimizing Casino Patron Loyalty Predicting Retail Customer Behavior Predictive Analytics for Email Campaigns Improving Retail Marketing Efficiency
Who To Contact Is Just the Start
In today’s complex marketing environment, finding your targets and providing the most enticing message to each will provide tremendous ROI for your marketing budget. This is the classic marketing optimization challenge. It has historically been very difficult to get right and perform efficiently, but with the advent of big data and efficient analytic tools like LityxIQ, it is now within reach.
There are many dimensions along which to optimize customer communications, channels, and budget decisions. For example:
- Cross-channel optimization. Most organizations have a segmented customer or prospect base with regard to preferred communication channels. Being efficient requires reaching your targets through their preferred channel or channels.
- Media mix optimization. The number of marketing channels is continually growing and the landscape is becoming more complex. It is important for a marketing organization to allocation budget optimally across channels in a way that accounts for both within channel performance, and cross-channel interactions.
- Offer and message optimization. Individual customers have individual preferences, and those preferences determine how they will react to the offer or message presented. Are they price sensitive? Offer sensitive? Have certain product affinities? Predicting and understanding their preferences and delivering tailored communication will lead to maximizing their response likelihood and long-term value.
- Data collection and experimental design. These approaches require a wealth of data… data that many organizations often do not have. For example, how do you know if a customer is price sensitive or not unless they have been offered multiple options in the past? Or which channel they prefer if they have only ever been targeted through one channel? While challenging, we provide techniques such as experimental design and uplift modeling to help provide the data resources to optimize channels and communications.
Optimizing Print Channel Acquisition Optimizing Casino Patron Loyalty
Healthcare & Pharma Analytics
Analytics Is Not Just For Marketing Any Longer
Increasingly, the healthcare, pharma, and life sciences fields are booming with transactional and outcome data ripe for analytics. Hospitals, healthcare providers, pharmaceutical reps, and scientists alike can leverage the power of modeling and advanced analytics to optimize their decisions and improve the lives of patients.
Our tools lend themselves to a variety of analytic solutions for these areas, including:
- Improving healthcare efficiency. Efficient healthcare provision leads to lower costs and optimal resource use. These can be informed through data and analytics. Reducing re-admission rate and predicting length of hospital stay are just a couple of examples that can lead to improved efficiency.
- Predicting risks and outcomes. Together, data and predictive models can provide an improved understanding of potential healthcare risks and outcomes. For example, a patient’s history combined with data collected through sensors can predict their risk for cancer. Or a hospital can use information from a patient’s current and prior hospital stays to predict risk of symptom re-occurrence.
Cancer Detection with Sensor Data
LityxIQ For Healthcare
Automated Analytic Processes
Efficiency in Advanced Analytics
It is not enough anymore to provide one-off analytic models or solutions. Analytic efficiency needs to extend from the initial stages of analytic projects all the way through implementation and ongoing processing. Our tools lend themselves perfectly to providing this full-lifecycle efficiency, and our OptyxIQ product is a great example of automation across the analytic lifecycle.
An automated analytic process often includes many or all of the following. Each is easily automated by LityxIQ.
- Automated data retrieval. Fresh prospect, customer, CRM, and transactional data is required to ensure models and analytic outputs are up-to-date. LityxIQ connects to secure data sources and automatically retrieves fresh information when it is available.
- Automated data management. Once fresh data is retrieved, many data management steps become necessary, including data cleaning, merging, filter, aggregation, and transformations. If this had to be done manually, all efficiencies would be lost. LityxIQ automatically sets off all required data management processes once fresh data is retrieved.
- Automated model scoring. Once data is available and processed, LityxIQ can be setup to automatically create fresh model scores (such as response, churn, or value) for all prospects and customers. No manual intervention, coding, or button-pushing is required.
- Automated optimization and media planning. If an optimal direct mail list, budget allocation, or media plan, are key analytic deliverables, these can be automated as well. Model scores and other optimization inputs such as costs and constraints can be automatically imported into the optimization process, then executed and exported. The plan can then be automatically pushed out to the client or their agency.
- Automated insights and reports. A closed-loop marketing process includes the ability to see fresh performance reports and new insights. LityxIQ can be setup to automatically update all performance reporting, dashboards, and other business intelligence outputs. If you have existing BI tools in place, data exports can be automated and then ingested into existing products.
Cost Benefit Comparison Predictive Analytics in Email Campaigns Cancer Detection with Sensor Data Improving Retail Marketing Efficiency
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