Empfohlen
Weitere ähnliche Inhalte
Was ist angesagt?
Was ist angesagt? (20)
Ähnlich wie Customer Analytics Overview
Ähnlich wie Customer Analytics Overview (20)
Kürzlich hochgeladen
Kürzlich hochgeladen (20)
Customer Analytics Overview
- 1. Customer Analytics Overview Jamie Renehan Customer Analytics @ BOI
- 2. Customer Analytics Life Cycle
- 3. Agenda • Why Customer Analytics Matter • Customer Journey Analytics • Customer Segmentation • Next Best Action • Sentiment Analysis • Customer Lifetime Value • Next Generation Analytics • Soft Skills in Analytics
- 4. Why Customer Analytics Matter • Engage each customer with consistent, personalized and seamless omni- channel communication. • Respond to customers in real time with one-to-one communications. • Increase sales and profitability by using customer context to determine the best offer for cross-sell and upsell opportunities. • Anticipate customer behaviour. • Monitor and track the effectiveness of marketing strategies across all channels, segments and products.
- 5. Customer Journey Analytics • A data-driven approach to discovering, analyzing and influencing your customers journeys that connects millions of events into journeys from your customers point of view. • Ability to deliver a personalized customer experience consistently across all channels and points of interaction. • Process of tracking and analyzing the way customers use combinations of channels to interact with an organization.
- 6. Customer Segmentation • Dividing customer base into groups of individuals that are similar in specific ways relevant to marketing, such as age, gender, interests and spending habits • Determine the revenue potential of each segment and target segments according to their profit potential and the ability of your company to serve them • Segment customers according to their stage of life so products can be tailored to their needs • Segmentation allows the marketing department to fine tune their approach and allows the product development team to tailor specific products for specific segments of customers
- 7. Customer Segmentation- Money Mindsets • Fjord’s four Money Mindsets define different people’s attitudes to spending and saving, segmenting them in a meaningful way. • ACHIEVERS:- In this mindset, people define success by budgeting for clear, often tangible goals. This helps them feel in control and prepared for the future. • BALANCERS:- In this mindset, people define success by getting the best deal in each transaction, maximizing rewards and staying on their financial plan so they don’t have to worry • EXPERIENCERS:- In this mindset, people define success by enjoying the present. They seek delight in how they choose to spend money and are optimistic about the future. • EXPLORERS:- In this mindset, people define success by saving money and making trade offs so they can be happy and live comfortably
- 8. Next Best Action • Ability to translate all the information you know about a customer into actions or interactions that make sense to the customer • Customer centric approach consuming interaction context, customer profile, analytics results, and a set of business rule to identify the most appropriate products or services to be presented and promoted to our customers • Driving long-term customer loyalty and value, while optimizing for business considerations – revenue, cost and profitability. • Be able to determine the most effective communication channel to facilitate customer engagement • Personalised marketing and experiences to improve marketing performance and enhance sale and service experiences
- 9. Sentiment Analysis • Campaign and Brand Sentiment Analysis to measure impact • Measure sentiment on Twitter, and other social media platforms on a weekly basis to evaluate the impact of marketing campaigns • Allows the analytics department to give objective feedback to marketing campaigns based on customers reactions on social media • Allows the marketing department to continuously adjust their campaigns to fit more to the target audience • The analysis is done using R and packages such as Rtweet and Rsentiment
- 12. Customer Lifetime Value • The Pareto Principle, also known as the 80-20 rule, posits that 80% of your sales come from just 20% of your customers. • One fifth of your customers are worth more to your business than all the others • Customer Lifetime Value Analytics gives us the ability to prioritize budgets, focus on retaining the right customers, and avoid wasting money and effort when you roll out targeted promotions • Need to understand your customers’ future value across multiple dimensions – current spend, cross-sell potential, loyalty and social clout, among others. • This information, combined with Advanced Predictive Analytics, helps determine a single metric, or dollar number, to more accurately quantify CLV.
- 13. The Next Generation of Analytics • Democratization of analytics • Leveraging new data types and sources - Semistructured and unstructured data. • From big data to fast data, reducing the time between data arriving and data value extraction, enabling real-time decision making. • Use of machine learning and other AI techniques to help analysts find patters in customer data, elicit recommendations for optimising performance. • Deliver the Right Offer to the Right Customer at the Right Time. performance. • Sharing of Analytics with customers (Revolut)
- 14. Soft Skills in Analytics • Problem Solving (find the root cause of a problem) • Critical Thinking (approach problem or task from multiple directions) • Storytelling (build a compelling and digestible story) • Communicating (present the results to engineers and senior executives) • Curiosity (never stop asking “Why?”, explore, investigate, gain knowledge)
Hinweis der Redaktion
- Customer Segmentation allows analysts to understand the landscape of the market in terms of customer characteristics and whether they naturally can be grouped into segments that have something in common. Customer Acquisition is used to acquire new customers and increase market share, and often involves offering products to a large number of prospects. Upsell/Cross Sell aim to provide existing customers with additional or more valued products. Upsell is the practice of selling more expensive products, upgrades or add-ons to an existing customer. Cross sell is the practice of selling additional products to existing customers. Next Product/Recommendation: When a company has many products to offer they have to determine which of those should be offered to a customer based on the existing products the customer owns. Next Best Communication Channel: Determine the optimal communication channel to reach prospects. Increase response rates, customer satisfaction and ultimately customer retention. Customer Retention/Loyalty/Churn aim at maintaining and rewarding customer loyalty and reduce customer defection. Reducing churn and building loyalty with retention strategies can significantly help grow your business. In the case of churn, we are looking for customers who will cancel a product within a certain time frame. Customer Lifetime Value models are used to design programs to appreciate and reward valuable customers. Customer lifetime value represents the expected revenue that is to be earned from the customer over her/his lifetime considering all of the possible products that this customer could purchase. Product Segmentation allows you to optimize product bundles using product affinity, in most cases using Market Basket Analysis. Market Basket Analysis is used to find product bundles.
- Engage each customer with consistent, personalized and seamless omni-channel communication in context. Respond to customers in real time with one-to-one communications – Pega's customer analytics solution consumes streaming data and events, tracks patterns and triggers actions to perform the optimal next-best-action based on your marketing strategies. Increase sales and profitability by using customer context to determine the best offer for cross-sell and upsell opportunities. Anticipate customer behaviors such as offer acceptance, credit risk and customer churn. Test scenarios and simulate results of marketing strategies before executing them. Differentiate your brand by consistently delivering unique propositions across every channel based on a deeper understanding of the customer's history and needs. Orchestrate all of the data, people, processes and systems required to automatically drive offers through to fulfillment. Monitor and track the effectiveness of marketing strategies across all channels, segments and products. Deeply understanding your target audience to anticipate their needs and desires.
- Gartner defines customer journey analytics as the process of tracking and analyzing the way customers use combinations of channels to interact with an organization and covers all channels present and future which interface directly with customers.
- Customer segmentation identifies groups of customers that are similar such that when you apply different service approaches to limited number of customer segments; it is the optimum compromise between the benefits of the centralised operations with the individual approach to each customer. Whether you are looking to determine new product offerings or develop a personalized marketing campaign, customer segmentation is the principal basis for allocating resources and extracting maximum value from both high and low-profit customers. Our experts use both demographic segmentation data and advanced clustering segmentation techniques to: Conduct market segmentation to unveil meaningful and measurable segments or microsegments according to customers needs, behaviors, demographics and social profiles Determine the revenue potential of each segment and target segments according to their profit potential and the ability of your company to serve them Obtain a complete customer profile to help predict future behavior through a 360° customer view Use target market analysis to tailor products, services, marketing and distribution strategies to match the needs of each segment Measure performance of each segment and optimize your segmentation approach over time
- Customer segmentation identifies groups of customers that are similar such that when you apply different service approaches to limited number of customer segments; it is the optimum compromise between the benefits of the centralised operations with the individual approach to each customer. Whether you are looking to determine new product offerings or develop a personalized marketing campaign, customer segmentation is the principal basis for allocating resources and extracting maximum value from both high and low-profit customers. Our experts use both demographic segmentation data and advanced clustering segmentation techniques to: Conduct market segmentation to unveil meaningful and measurable segments or microsegments according to customers needs, behaviors, demographics and social profiles Determine the revenue potential of each segment and target segments according to their profit potential and the ability of your company to serve them Obtain a complete customer profile to help predict future behavior through a 360° customer view Use target market analysis to tailor products, services, marketing and distribution strategies to match the needs of each segment Measure performance of each segment and optimize your segmentation approach over time
- Next-best-action is the ability to translate all the information you know about a customer into actions or interactions that make sense to the customer, driving long-term customer loyalty and value, while optimizing for business considerations – revenue, cost and profitability. The principle of next-best-action is a critical step in marketing to individuals. As customers increasingly dictate the terms of their interactions with businesses, it is crucial to make that interaction as personalized and relevant as possible. Enterprises that aren’t using next-best-action are leaving money on the table: missing opportunities to upsell or early warning signs that a customer will switch to a competitor.
- Sentiment Analysis: How do customers feel about your brand and why is it important? A sentiment analysis takes an overall look at what people are feeling about your brand.
- Sentiment Analysis: How do customers feel about your brand and why is it important? A sentiment analysis takes an overall look at what people are feeling about your brand.
- Sentiment Analysis: How do customers feel about your brand and why is it important? A sentiment analysis takes an overall look at what people are feeling about your brand.
- Customer lifetime value (CLV) is the expected value of the future relationship with a given customer. The potential value of a group of customers or of the entire customer base is called customer equity. The calculation of customer lifetime value has four components: lifetime duration, cash in, cash out and the discount rate as illustrated below. Based on the input data, we build customer micro-segmentation and customer profitability model using homogeneous Markov chains. The CLV model can be used together with a churn model in a matrix to identify the target group eligible for a marketing action, which is usually a contact with a special offer.
- Better customer analytics, thanks to machine learning. Start with a proof of concept Utilize disparate data Democratization of analytics Simplified real-time analytics applications. “From big data to fast data” Fast data reduces the time between data arriving and data value extraction, enabling real-time decision making. Fast data is data in motion. Fast Analytics on Fast Data: becoming more real-time by collapsing the distance between data collection, insight and action. Analytical models will become embedded right in the operational application, directly influencing business outcomes as users interact with them. The need to maintain data pipelines to move data and ensure synchronization between storage systems. Fast data for event-driven analytics: Gain deeper insights and enable rapid responses by leveraging real-time data ingestion and analytics at-scale. “Fast data means smarter analytics” Artificial Intelligence will be essential for analytics: Use machine learning and other AI techniques to help analysts find patters in customer data, elicit recommendations for optimising performance, and allow non-professionals to access complicated analytics using simple language. Chatbots for customer intelligence Rise of chatbots. Bots and customer analytics to combine to increase customer value. Chatbots become more crucial in digital engagement sphere Natural-language interfaces Unified Digital Analytics: Unify the disparate services and disjointed UI’s that span the Digital Analytics suite. Deliver the Right Offer to the Right Customer at the Right Time. Add Customer Value in Real-Time. (Real time offers, inventory optimization) Sharing Analytics with your customers (Revolut) Graph Analytics Leveraging new data types and sources - Semistructured and unstructured data continue to be under-exploited by marketing organizations, and this needs to come to an end. The technology and tools are in place and available today to enable analysis of these data sources.
- Problem Solving https://www.lynda.com/Business-Skills-tutorials/Problem-Solving-Techniques/553700-2.html Critical Thinking https://www.lynda.com/Business-Skills-tutorials/Critical-Thinking/424116-2.html Storytelling https://www.lynda.com/Excel-tutorials/Data-Visualization-Storytelling-Essentials/435230-2.html Communicating https://www.lynda.com/Leadership-Management-tutorials/Communicating-Confidence/359601-2.html Cultivating curiosity https://www.lynda.com/Business-Skills-tutorials/Cultivating-curiosity/185320/414081-4.html