This document discusses customer lifetime value (CLV) in digital marketing. It defines CLV as the present value of the future cash flows from a customer. For e-commerce companies, predicting customer behavior and future profit is more difficult than for companies in industries like telecommunications that have more predictable customer cash flows. The document provides examples of how CLV can be used to focus marketing efforts on profitable customers, evaluate direct marketing campaigns, and integrate customer data from CRM systems into digital advertising platforms like Google Ads to optimize bidding and targeting.
Toployaltyprogram.com offers a complete loyalty solution for businesses that includes a custom mobile app for customers, integration with social media and messaging to engage customers, and tools to capture customer data and send targeted communications to strengthen customer relationships and drive repeat business. The solution aims to provide a more effective alternative to paper-based loyalty programs and basic POS systems by offering customized mobile and online features with analytics and marketing capabilities. Businesses can start by visiting toployaltyprogram.com to request more information and get a customized proposal.
This document argues that investing in a full digital marketing funnel, including upper and lower funnel tactics, yields better results than using just lower funnel tactics alone. It summarizes an analysis of campaign data from multiple DSPs that showed upper funnel tactics like prospecting positively influenced lower funnel strategies like remarketing by driving more users and clicks into the remarketing pool, increasing reach and conversion rates. Specifically, campaigns using a full funnel approach saw 64-110% higher conversion rates than remarketing alone. The document concludes that combining upper and lower funnel tactics increases conversion volumes through incremental conversions.
This document outlines an agenda for a B2B marketing summit on account-based marketing segmentation. The summit will cover building a priority account list, segmenting techniques, and goal setting. It discusses gathering stakeholders to identify the most valuable customer accounts and attributes to focus on. The process of prioritizing, iterating, and maintaining the account list is described. Finally, it discusses connecting marketing technologies to different goal types like engagement, attraction, and conversion for each account segment.
This document discusses various aspects of customer relationship management (CRM) strategies including customer loyalty, satisfaction, and retention. It covers topics such as the different types of customer loyalty; factors that influence satisfaction and loyalty; developing loyalty profiles; and strategies for acquisition, retention, and winback. Some key points include: there are behavioral and attitudinal aspects of loyalty; satisfaction alone does not ensure loyalty; preferential treatment, rewards, and personalization are examples of retention strategies; and winback strategies aim to regain customers who have defected.
This presentation provides insight into how to forecast and calculate customer lifetime value (CLV). Here a startup applied a scientific approach to maximise customer retention and minimise churn. The outputs of the analytics were built into the system and business processes driving the success of the company and helping it to win the customer service of the year award, and to achieve a successful exit through acquisition.
This presentation discusses customer lifetime value (CLV) modeling. CLV is defined as the net profit attributed to the entire future relationship with a customer. It is typically used in business-to-consumer contexts but can also apply to business-to-business. CLV must be greater than customer acquisition costs. The presentation outlines different levels of sophistication in CLV prediction models and lists key inputs like contribution margin, churn rate, retention cost, and period. It provides a simple e-commerce example and discusses how churn rate strongly impacts CLV for subscription businesses. Standard and more accurate CLV calculation formulas are also shown.
This document discusses customer relationship management (CRM) strategies and implementation. It covers CRM strategy topics like understanding customer needs, reducing churn, and increasing revenue. It also discusses CRM implementation topics like planning, product selection, data migration, and hosting. The overall document provides guidance on developing a comprehensive CRM strategy and successfully implementing a CRM system.
1) Customer relationship management (CRM) is a strategy that places customers at the center of a business to foster mutually beneficial relationships. It requires understanding key CRM concepts and best practices.
2) Calculating a customer's lifetime value allows businesses to segment customers, focus on the most profitable, and tailor offerings. However, each customer desires unique relationship styles so one approach does not fit all.
3) Businesses can increase customer lifetime value by reducing defection rates through personalized service, strengthening relationships, and cross-selling/up-selling additional products. The goal is satisfying customers so they remain loyal and generate future profits.
How to Create a Customer Segmentation ModelMark Haubert
Are your sales and marketing teams focused on the right customers? Learn how to define your Ideal Customer Criteria, create a Customer Segmentation Model, identify your Key Accounts and focus your teams on customers with the greatest potential for growth.
8 Pillars of Demand Generation InfographicScott Levine
The 8 Pillars Of Demand Generation
An Infographic of the Modern Demand Generation Ecosystem
Demand generation and lead generation are often used synonymously, but they are actually quite different.
The 8 Pillars of demand generation were developed to address a wide range of topics that include everything from building awareness to sales enablement.
Demand generation is typically a multistep integrated marketing and sales process that varies in size and scope based on sales complexity. Demand generation can include building awareness, positioning and consumer research to support purchase behavior, sales enablement, customer onboarding and post-sale customer satisfaction.
Lead Generation: Strictly speaking, lead generation is the process of generating interest in a product or service. Typically, leads are gathered to build a list that provides contacts for sales.
Our Demand Generation Program Playbook is a planning methodology that highlights our premium tool-kit of tools & templates to help you develop and implement a demand generation strategy that provides a steady flow qualified, engaged leads for your sales team.
Lifetime Value (LTV) can help your entire company understand the actual value that you can expect to receive from a single customer over the course of your relationship with them. It is the metric that tells you whether customers are happy and enjoying your product or that customers are ready to churn and you should reassess your strategy.
Here we walk through exactly how to calculate Lifetime Value (LTV), including what to and not to include in the calculation, as well as how to optimize this crucial SaaS metric.
Sales & Marketing Development Plan - a template for the CROFan Foundry
The document is a Sales & Marketing Development Plan template that outlines four major parts: Sales and Distribution Strategy, Customer Development Program, Strategic Marketing Framework, and Integrated Marketing Plan. It provides sample content and suggested key performance metrics for each section to help users develop their own customized plan. The template comes as a PowerPoint file that can be tailored for a user's specific needs.
This document summarizes the work of a team that conducted customer segmentation, lifetime value modeling, and recommendations based on the analysis. The team segmented customers using RFM analysis and descriptor variables, identified 7 segments with different characteristics and churn rates. They then modeled customer future value and found segments with high, medium, and low future values. The recommendations target migrating customers between segments to increase revenues.
This document discusses strategies for increasing the lifetime value of customers. It begins by explaining how to calculate the annual profitability and lifetime value of customers. Customers are assets that provide future cash flows, so acquiring and retaining customers is important. The document then outlines 11 strategies for increasing a customer's lifetime value, such as increasing purchase frequency, sales amounts, customer retention, and developing new products/services that appeal to existing customers.
Your monthly or annual recurring revenue (MRR and ARR for short) is one of the primary reason we're all in SaaS. Recurring revenue means our growth can compound and through this momentum we can ensure we're always improving and building something beautiful.
Here we walk through exactly how to calculate Lifetime Value (MRR/ARR), including what to and not to include in the calculation, as well as how to optimize this crucial SaaS metric.
• 3. The 3 Models of SaaS Pricing1How to Pick the Best Price28 Pricing Hacks3How to Test New Pricing4We’ll cover...
• 4. Model 1: Targeting Small Businesses1
• 5. Self-service, no sales team, limited support
• 6. Pricing in the $10 - $100/month rangeThis mean you need to focus onscale and acquiring customerscheaply.
• 7. Similar companies
• 8. Model 2: Targeting Enterprise2
• 9. Sales team, contracts, full support
• 10. Pricing is $1,000s or $10,000s/monthVery little is automated, your teamwill be working very closely witheach customer.
• 11. Similar companies
• 12. Model 3: The Mid-Size Hybrid3
• 13. Automated marketing with a sales team
• 14. Pricing is $100’s/monthYou’ll need to scale your leads butyou’ll have a full sales team toclose them.
• 15. Similar companies
• 16. Pick the right price range for your vision
• 17. 2 Bad Methods for Pricing
• 18. 1. Product cost + X%You’ll undercharge somecustomers and overcharge others.
• 19. 2. What does the customer want to pay?People have no idea until you askthem for their credit card.
• 20. Pricing by Value
• 21. Value-Based PricingYour customers get value worth $Yand it only costs them $X.
• 22. For B2B, focus on money earned or saved
• 23. How much extra revenue do they earn?1How many hours do they save?2What other costs do they avoid?3Ask your customers:
• 24. Capture more value from each customer.
• 25. There’s no such thing as a perfect price.If you need more guidance, pick aprice that’s 10% of the valuedelivered.
• 26. 8 Pricing Hacks8
• 27. Rule 1: Go AnnualYou’ll improve cash flow, reduceyour churn, and improve yourrevenue.
• 28. Rule 2: Don’t Add Unnecessary Digits$1000 looks cheaper than $1,000or $1000.00
• 29. Rule 3: Avoid Discounts Unless LaunchingDiscounts create destructivecustomer habits. Do not use themregularly.
• 30. Rule 4: Offer Multiple Prices to Anchor
• 31. Rule 5: Use pricing plans to segment customers.Different customer types getdifferent value from your product.Capture that value.
• 32. Rule 6: Double Your PriceWe all tend to UNDERvalue our ownservices.
• 33. Rule 7: Be Careful With Freemium PlansVery difficult to make it work in B2Bmarkets.
• 34. Rule 8: Grandfather Old Customers InAs long as you don’t raise pricesfor old customers, you won’t getany complaints.
• 35. These are rules, not laws.
• 36. How to Test New Pricing - 4 Steps
• 37. Step 1: Track subscription plans for all customersSubscription plans1Each monthly charge2Any cancelations3Access to total revenue, averagerevenue per user, and churn4
• 38. Step 2: Launch Your New Pricing Page
• 39. Step 3: Track your entire funnel
• 40. Step 4: Track ARPU and churn
• 41. KISSmetrics helps you find the right priceConnects all data to individual people1A/B tests for your entire funnel2See which plans are most profitable
Co je nového v prediktivní analytice, a co nového teprve bude? Jak se na to připravit? A s čím je možné začít už dnes? Od hlubokých neuronových sítí po obyčejnou obsluhu zákazníka v obchodě.
Detailní case study s konkrétními daty o realizaci user scoringu v závislosti na průchodu uživatele webem napříč návštěvami a interakcemi s obsahem a jeho následné využití ve výkonnostních kampaních.
Každá implementace je jiná, ale některé problémy se přesto opakují. Pár praktických tipů, na co si dát pozor, jak se situací vypořádat a možná ušetřit. Vaše data si to zaslouží.
Obliba mobilních aplikací v poslední době stoupá stejně rychle jako obliba mobilních webů. André ve své přednášce ukáže, v čem je takové měření odlišné, jak se k němu postavit a na co si dát pozor.
Pět tipů pro agentury, kterak ošidit své klientyTaste Medio
Ve skutečnosti pět tipů pro majitele e-shopů a provozovatele webů – o čem se bavit se svou agenturou, jaké reporty od ní chtít, co si pohlídat a na co si dát pozor.
The document discusses customer lifetime value (CLV), including:
1. CLV is the predicted net profit attributed to the entire future relationship with a customer.
2. CLV is an important metric because the best customers account for the majority of sales, and retaining existing customers is often cheaper than acquiring new ones.
3. Companies can use CLV to inform customer acquisition and relationship management strategies, such as spending more to acquire or retain the most valuable customers.
Možnosti lokační analýzy pro e-commerce. Koho rekrutuji do zákaznické báze a odkud. Proč to tak je? Proč nezískávám jiné zákazníky? Prostorová segmentace jako základ pochopení vlastní zákaznické báze.
Video z přednášky: https://www.youtube.com/watch?v=pmxAfrcQHKY
Enhanced Ecommerce je funkčnost Google Analytics, skrz kterou se do systému dostává řada velice užitečných rozšiřujících dat a informací. Přestože už je nějakou dobu k dispozici, využívá ji dosud překvapivě málo e-shopů. Pojďme se proto společně podívat, o co vlastně jde, k čemu je Enhanced Ecommerce dobré, v čem vám může reálně pomoci a jak to celé dostanete i do svých Google Analytics.
Když už dneska někdo rozesílá e-maily, nejspíš se už dívá na základní metriky každé kampaně. Sleduje v mailingovém nástroji open-rate a click-rate, vyhodnocuje v Google Analytics na počty návštěv a přivedených konverzí. Pojďme se spolu podívat na e-mailingová data hlouběji. K čemu všemu se také dají využít a jak s nimi lze ještě pracovat?
Vybrané e-shopářské vychytávky z Google AnalyticsTaste Medio
Užitečné ecommerce příklady, o kterých jste ani netušili, že se dají v Google Analytics řešit. Sledování 404 chyb, sofistikovanější vyhodnocování vyhledávání a filtrací, smysluplnost interních bannerů a cross-sellingu apod. Vžijete se do kůže potenciálního zákazníka a zaostřete na klacky, které mu svým webovým řešením hážete pod nohy.
This presentation was given at the 2013 edition of Sitecore’s Digital Trendspot event at the Emirates Stadium. The deck asks ‘Who exactly are a brand’s ‘lifetime customers’ and what do we do with them?’. In answering this question, the power of ‘Known Peer Influence’ is examined, along with a number of tactics and strategies for finding the people that are truly evangelistic about your brand, and growing their loyalty and influence.
RFM analýza patří k základním metodám segmentace zákazníků. Je poměrně jednoduchá na pochopení i přípravu, kdokoliv si ji může během půl hodiny udělat třeba i v Excelu. Přesto o ní řada webů a e-shopů neví nebo ji nepoužívá. V průběhu přednášky si ukážeme, o co vlastně jde a jak RFM segmentaci připravit. Na řadě konkrétních příkladů si pak demonstrujeme, jak ji využít ve svém marketingu, e-mailingu, remarketingu či zákaznické komunikaci.
Pět reportů, které by e-shopáři měli řešit a neřešíTaste Medio
Provozovatelé e-shopů už se v posledních letech naučili, že na webu je potřeba mít nasazený nějaký analytický nástroj. Že bez něj jsou slepí a vůbec netuší, kolik mají návštěvníků, odkud přicházejí a co dělají. Přesto si i nadále často nejsou jistí, na která čísla se vlastně dívat a co si z nich odnést.
V přednášce si ukážeme a vysvětlíme pět pohledů na e-shopová data, které budou pro většinu jejich provozovatelů klíčové a zásadní, ale přitom je zatím sleduje a vyhodnocuje málokdo.
Metrics How To: Ratio of Customer Lifetime Value to Customer Acquisition CostFiresnap, Inc.
The document discusses the ratio of customer lifetime value to customer acquisition cost (LTV:CAC) metric. LTV:CAC compares the total value a customer provides over their lifetime with a company to the costs to acquire that customer. Calculating LTV:CAC allows companies to assess return on investment from customers and make more informed growth strategies. The document provides steps to determine LTV:CAC, including calculating customer lifetime value and comparing it to customer acquisition cost.
Customer Acquisition Cost and Lifetime Value (CAC & LTV)Sarah Wilz, M.Ed
This document discusses customer acquisition cost (CAC) and lifetime value (LTV), two key metrics for evaluating the financial performance of acquiring customers. It defines CAC as the cost to acquire a new customer and LTV as the total revenue generated by a customer over their lifetime. It provides formulas for calculating CAC, LTV, and the CAC payback period. A CAC/LTV ratio of at least 3x and payback period of 12 months or less are recommended targets. The document explains why these metrics are important for investors, bootstrapped companies, and reducing equity dilution. It addresses common questions about including costs in CAC calculations and estimating customer lifetime.
Customer Lifetime Value: The Core Metric in MarketingAdknowledge
How to use data and lifetime value to maximize the ROI on your marketing spend.
Out of all the metrics that we monitor in our business, there is one that captures the heart, soul, and ROI of our efforts: lifetime value (LTV) of our customers. The measurements of digital marketing have evolved dramatically over the years from CPM to CPC, CPA, CPI, and more. The next phase, and perhaps the most important, is calculating LTV. Few are taking the leap to position this metric as the core KPI of their marketing teams’ success. But the reality is, the moment your competitor starts to figure out LTV and you can’t, you’re dead.
In this session, Ben outlines best practices for developing the strategy necessary to undertake calculating lifetime value to better understand your customers and the essential analytics you need so you can boost your ROI.
Zodiac & InfoTrust Webinar: The Basics of Customer Lifetime Value 5.9.17ZodiacMetrics
Dr. Peter Fader, co-founder of predictive analytics company Zodiac and marketing professor at Wharton, teams up with CMO Michael Loban of web analytics consultancy InfoTrust to explain the basics of using Customer Lifetime Value (CLV) and predictive analytics to supercharge your marketing and business strategy.
The presentation covers-
-The definition of Customer Lifetime Value (CLV)
-Why CLV is meaningful to your organization
-How to think about calculating CLV and why many methods are incorrect
-How to use CLV and predictive analytics to optimize your strategy and campaigns
-Common questions and concerns
Calculating Customer Lifetime Value How-To GuideDemand Metric
Executive Summary
This How-To Guide details the definition of customer lifetime value (CLV), the advantages of calculating CLV and the standard formula for calculating CLV.
Common sense tells us that the longer a customer is in relationship with a company, the more profitable that customer relationship is. However, many companies put the emphasis on new customer acquisition and not enough effort is made to retain existing customers. This is a mistake, because the financial impact of retaining customers is substantial: companies can increase profits by as much as 100% by retaining just 5% more of their customers. For these reasons, CLV is a crucial metric that most organizations overlook mainly because its definition and purpose are not entirely known. Understanding the monetary value each customer represents to your organization can help you budget correctly for your business needs, strategically plan your marketing initiatives and improve long-term relationships with your customer base.
Read this brief 4-page guide to learn about:
Customer Lifetime Value
The advantages of calculating CLV
The standard formula for calculting CLV
Use the Customer Lifetime Value Calculator to get started!
Demand Metric's How-To Guides are designed to provide practical, on-the-job training and education and provide context for using our premium tools & templates. If there is a topic that you would like to see covered, please contact us at info@demandmetric.com (link sends e-mail) to make a content request.
This document provides an overview of a workshop on using Smart Bidding to align business goals with Google ads. The workshop covers:
- Why value-based bidding is important for businesses to optimize based on the true value of conversions rather than just volume or cost.
- Different options for Smart Bidding, including both non-predictive and predictive approaches, to maximize results based on business metrics like revenue, profit or lifetime value.
- Examples and case studies of how to implement value-based bidding for different business types like online retailers, lead generators, and agencies. This includes integrating first-party data signals into bidding to improve performance.
The retailer wanted to create a unified customer data platform to provide complete visibility across their customer's omnichannel touchpoints and move from siloed data to a 360-degree view. Tredence helped build a CDP that integrated over 70 data sources, processed 250TB of data weekly, and increased addressable customer data visibility by 14%. This allowed the retailer to put the customer at the center of decisions, optimize their $3B marketing budget, and win a larger share of partners' advertising dollars in a cookie-less world.
This document provides an overview of B2B sales methodology, CRM, pipelines, and key metrics. It discusses how CRM aims to maintain customer records but has not fully solved executive and sales challenges. The document outlines different stages for designing a sales funnel and pipeline, as well as automation tools that can enhance the pipeline. Key sales metrics covered include cost per lead, average opportunity size, pipeline velocity, weighted opportunities, customer acquisition cost, conversion rates, retention rates, customer lifetime value, and net promoter score.
Watch This Free Webinar On-Demand: http://dg-r.co/2fuk0LO - Maximize Customer Lifetime Value In 2017 by Leveraging Your 2016 Wins
Learn why Customer Lifetime Value is a critical metric that can improve your ABM plan & shape your 2017 budget
You worked hard in 2016 to target and convert the accounts and prospects with the highest propensity to buy. Now you need to keep those new customers happy while continuing to expand those relationships. Join Matt Zelen, SVP of Customer Success at Act-On Software, and learn how you can maximize your customer lifetime value in 2017, including:
• Why customer lifetime value is a vital strategic metric for your business;
• How both customer lifetime value and customer acquisition can help determine marketing budget in 2017;
• Tips and tricks to creating a long-term, strategic approach to defining customer lifetime value; and
• How CLV positively impacts account-based marketing initiatives.
CLV Advertising & Marketing Strategies to Acquire and Retain Consumers With P...Tinuiti
In today’s digital landscape, it’s crucial to adapt your business to this new wave. Improve the customer shopping experience, understand complexities of CLV, realize how to utilize customer shopper behavior data, all to attract, acquire & retain the most profitable customers for your company’s long-term. Join this session as we cover advanced Paid Search customer retention strategies that’ll help you to drive revenue & loyalty for your Ecommerce business.
Francesco Federico, Global Digital Marketing Director at Acer, discussing: Integrating real time predictive analytics in marketing strategy at the iMedia Data Fuelled Marketing Summit, London, Feb 2016.
http://www.imediadatasummit.co.uk/
Holistic View of Consumer Data Across an Integrated Media Strategy to Accurat...Tinuiti
Each client’s customer, marketing efforts, products, are different. It takes advanced analytics and machine learning to understand and predict preferences and behaviors. A system that makes it easy to activate those insights in ways that help brands acquire more high-value customers, accelerate loyalty within the customer base, and intervene when customers begin to veer off their expected purchase journey. When it comes to measuring your CLV, you should consider these variables for the most accurate results. In this session, we’ll touch on data hygiene, client examples, what it takes to accurately report and measure CLV.
How to guide - calculating clv (sample)Jesse Hopps
The document discusses calculating customer lifetime value (CLV), which is defined as the net present value of the cash flow from a customer over the entire relationship. Calculating CLV provides benefits like valuing customer relationships, evaluating proper investment in each customer, and emphasizing long-term relationship cultivation. The standard CLV formula uses variables like gross profit margin, repurchase rate, and interest rate. The document recommends identifying these variables, calculating CLV for customers, highlighting patterns, and using CLV for marketing and sales planning.
Actionable Steps to Increase CLV Across Your Integrated Media StrategyTinuiti
Each client’s customer, marketing efforts, products, are different. It takes advanced analytics and machine learning to understand and predict preferences and behaviors. Discover the most effective strategies that top brands are using to increase CLV with a holistic view of other channels to inform their integrated media strategy.
Optimizing Your Digital Marketing CampaignsIdea to IPO
Arjun Dev Arora, founder and chairman of ReTargeter, provides an overview of optimizing digital marketing campaigns. He discusses core metrics like impressions, clicks, conversions and their importance in measuring campaign performance. He also covers core dimensions to optimize like inventory sources, creatives, time of day and landing pages. Additionally, he outlines intelligent spending approaches like CPM, CPC and CPA models. The document provides execution and optimization best practices including testing creatives, using first party data and real examples testing time of day targeting.
Customer Experience Matrix Mechanics and Geeky CRM Cx CEMClient X Client
Customer and marketing analytics using CxC Customer Experience Matrix as rules framework. Big data, omnichannel and multichannel marketing, programattic markiting, CRM and internet of things make customer management, campaign management business processes exponentially more complex requiring a Customer Experience Framework, The CxC Customer Experience Framework enables managers to "automate what works and spend their time innovating."
RADAR - Customer Value Optimization as a Service v2.pptxAlexandre Chaves
1) RADAR provides a customer value optimization framework to help companies maximize the lifetime value of their customers through personalized experiences and marketing.
2) The framework includes gathering customer data, profiling customers, segmenting them by value, targeting customers at different lifecycle stages with customized messages and offers, and actively listening to feedback to continuously improve the customer experience.
3) The goal is to develop long-term, loyal relationships with the most valuable customers to drive sustainable business growth and shareholder value.
Multichannel Retention Strategies: A Steady Diet of Low Hanging FruitVivastream
The document discusses identifying customer churn and measuring lifetime value. It provides a real-world example of an effective multi-channel retention campaign utilizing analytics and a cost-progressive channel strategy. Specifically, it describes how a wireless provider used business intelligence to target likely churn customers and employed a multi-channel strategy including text, direct mail, and calls to increase retention rates and ROI. The campaign resulted in a 5.6% reduction in churn and a 180% increase in ROI compared to a basic segmentation strategy.
The document discusses applying decision science techniques to solve various business problems in customer relationship management. It covers topics like prospect targeting and acquisition, customer segmentation, profitability and loyalty analysis, cross-selling and upselling strategies, campaign management, customer lifetime value analysis, and customer retention through churn management. Decision science helps businesses make targeted decisions at each customer lifecycle stage to optimize acquisition, usage, retention, and customer lifetime value.
2014 Customer Loyalty ASEAN Conference: Prof de los ReyesJim D Griffin
1. Segmentation plays a key role in loyalty marketing by dividing customers into groups based on common attributes and behaviors. This allows companies to better understand their customers and maximize relationships.
2. There are various levels of segmentation from basic demographics and purchases to more advanced psychographics and transaction data. Companies can use both supervised and unsupervised segmentation.
3. Effective segmentation identifies strategic business focuses, provides insights into customer needs, and helps companies focus communications and campaigns. It is a process that aims to create meaningful customer groups.
These slides are an extract from a workshop on Saas Analytics I gave in collaboration with the Dutch National Association for Private Equity and Venture Capital. In there, I explain how to create a frame of analysis for Saas Businesses starting from understanding the customer dynamics and then identifying the right metrics for the case.
- Customer Value Optimization (CVO) aims to maximize customer value by creating great journeys for valuable customers through extensive personalization.
- CVO involves understanding customers through profiling, segmenting them based on lifetime value, and targeting them at different lifecycle stages with customized messages.
- RADAR is a CVO framework that focuses on retaining high-value loyal customers, developing customers with growth potential, and reactivating at-risk customers.
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Matouš Ledvina na PPC Date #3. Používáte smartbidding? A pokud ano, používáte ho správně? Společně se můžeme podívat na to, jak vypadají automatizované kampaně podle standardu roku 2021 nebo třeba proč volná shoda není sprosté slovo.
Jan Tichý na PPC Date #3. Doba, kdy dosavadní staré Universal Analytics jednou provždy nahradíme novými Google Analytics 4, se nezadržitelně blíží. Pojďme si shrnout, co tahle změna znamená pro pépécečkaře. Namísto přenesení stejných postupů na nový nástroj to využijme jako příležitost, jak začít dělat věci úplně jinak a lépe.
The document discusses how to work with keyword analysis to improve search engine optimization. It provides examples of how keyword analysis can be used to track keyword trends over time, calculate expected investment returns, structure campaign categories, identify low search volume keywords, better understand product demand, and help create website content. The document also shows how keyword data can help specialists set annual collaboration plans, build marketing plans and benchmarks, analyze keyword category seasonality, calculate campaign expected conversions and returns on ad spend. It emphasizes structuring campaigns based on search volumes and creating landing pages to improve targeting, quality score, lower costs, and increase conversions.
Vyhodnocování tendrů aneb insighty z B2B průzkumůTaste Medio
El documento proporciona información sobre Rival Up, una compañía que ofrece servicios de investigación de mercado y marketing a otras empresas. Rival Up realiza encuestas telefónicas y de correo electrónico para ayudar a las empresas a comprender mejor el mercado en el que operan y adquirir nuevos clientes. También comparan las ofertas de los clientes con la competencia para identificar áreas de mejora.
Právní bitvy o PPCčka aneb věděli jste, že...?Taste Medio
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1.4 Quantitative vs. Categorical Data,
1.5 Big Data vs. Little Data, Data science process
1.6 Role of Data Scientist
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8. CAPI questions and texts
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Long-term oxygen therapy (LTOT) and novel techniques of evaluating treatment efficacy have enhanced the quality of life and decreased healthcare expenses for COPD patients.
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Signals & Telemetry Annex K for RBF's The World Game / Trade Federations / USPTO 13/573,002 Heart Beacon Cycle Time - Space Time Chain meters, metrics, standards. Adaptive Procedural template framework structured data derived from DoD / NATO's system of systems engineering tech framework
3. Confidential & Proprietary
“ Customer centricity is a strategy that
aligns a company’s development and
delivery of its products and services with the
current and future of a select group of
customers in order to maximize their long-
term financial value to the firm ”
4. Confidential & Proprietary
Focusing on profitable customers
% of Total Customers (sorted by profit)
%ofTotalProfit
ID 123
When there is a large heterogenity in your customer base
in terms of profits that your customers bring you or
losses you can count, you need to focus on selecting
such segments. Create a Pareto chart like this using
Tableau.
5. Confidential & Proprietary
“ Customer Lifetime Value (CLV) is the
present value of the future (net) cash flows
associated with a particular customer “
“ Customer Equity is the sum of customer
lifetime values across a firm’s entire
customer base“
noca.cz/clvbook
8. Confidential & Proprietary
How easily can you predict customer behavior?
History Present Future
Customer 1
Customer 2
Customer 3
Transactions in the learning period
9. Confidential & Proprietary
E-commerce settings
Focus on end customers (B2C)
Non-contractual settings
Non-membership status
Always-a-share (vs. lost-for-good)
Continuous buying
Variable-spending environment
Partial identification possibilities
11. Confidential & Proprietary
Reports of lifetime value in Google Analytics serve
its own purpose
support.google.com/analytics/answer/6182550?hl=en
12. Confidential & Proprietary
How does CLV look like in reality?
For each customer you typically estimate lifetime profit
(discounted in following years).
I’ve found out that for better actionability it is useful to
estimate profit for some shorter term: ¼ to 3 years. This
should be selected depending on the nature of business
when your customer have high probability of
repurchasing.
Also, you typically calculate CLV each month/week/day in
order to see how your predictions evolve.
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Your monthly calculations for each
customer. Naturally, CLV models
change when customer purchases and
“fade out” the value when the customer
is inactive.
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Levels of CLV that you might use
Trend of exact values: 107 CZK → 123 CZK
Current exact value: 123.45 CZK
Bucket: CLV High (3000+ CZK)
16. Confidential & Proprietary
The simplest way to estimate CLV:
sum up profits by acquisition cohorts
Gross Profit for all customers
18. Confidential & Proprietary
Can you choose CLV as your KPI?
CPA
ROAS
Profit
Revenue
Value Optimized
ROI and Total
Profit Optimized
Conversions
Cost Optimized
PNO
(CtRR, ERS,
COS)
Conversions
Cost Optimized
Long term
Profit
Customer Equity
Customer Lifetime Value
Optimized (CLV)
Can you manage and optimize CLV
directly? Or do you need to speak in
terms of CPA and ROAS with your
advertising platform?
19. Confidential & Proprietary
Simplifications of
marketing activities
Seeing all touchpoints
Attribution of conversions and costs
Word of mouth and referrals
Cross-environment behavior
(cross-device, omnichannel)
External and indirect effects
Individual campaigns vs. portfolio
approach
Simplifications of
customer data
Future incremental purchases
Past behaviour of a customer
(new customer?)
Variable spending
Volume of sales
Averages vs customer heterogeneity
Data in the right moment
At each step, you come across many simplifications
20. Confidential & Proprietary
When a path is the goal
P | alive
Monthly or annual repurchase rate
Ratio of new customers
Ratio of profitable customers
Number of customers with annual profit of 1000+
You can benefit from customer centric
KPIs while not talking directly about
CLV. Don’t hesitate to start with
examples like this at first phase.
22. Confidential & Proprietary
Main areas where online marketers
can benefit from CLV
Theoretically:
➔ Customer Acquisition - Expansion - Support - Retention
➔ Direct Campaigns
➔ Customer Intelligence (CRM, managerial reporting)
Ideas of use cases like those mentioned on The Wise Marketer, on Econsultancy
and Custora are nice, but lack details.
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1) Customer Acquisition
How much can we afford to pay for a new customer? What is the true value per
acquisition? Should that influence CPA / ROAS targeting?
What products drive higher CLV?
How fast can we estimate CLV for a fresh user/customer?
When can we compare CAC and Historical Profit + CLV?
24. Confidential & Proprietary
Kevin Hillstrom
There is a direct correlation
between annual repurchase rates
and the length of time you are
willing to wait for payback.
http://blog.minethatdata.com/2015/10/lifetime-value.html
25. Confidential & Proprietary
2) Customer Expansion
For what segments of customers should we increase/decrease marketing
activities (/costs)? When?
When can we push marketing efforts on fresh customers?
What is the impact of (up|x)-selling on CLV?
What less profitable customers should we remove from mailing?
What if CLV estimation rises?
26. Confidential & Proprietary
3) Customer Support
Should we give a customer a gift or an exclusive deal?
Who can (not) be given a discount?
Who should wait in a queue for a support?
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4) Customer Retention
How much can we afford to pay to retain a customer and still being profitable?
What to do when CLV estimation drops?
How to treat customers with low or negative CLV?
Should we give incentives when CLV rises?
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5) Evaluate Direct Campaigns by change in CLV
Decide which customers by CLV to select for a campaign.
Can we get top 10% customers by CLV?
Use ratio of CLV as max costs per campaign.
29. Confidential & Proprietary
6) Customer Intelligence and managerial reporting
of your customer base
Where will high profits come from? What are profit drivers?
How well can we forecast sales?
How does CLV/Customer Equity evolve? For various companies, markets,
customer types, segments of customers.
What activities can you do to support the growth?
31. Confidential & Proprietary
Actionability concerns
Reporting vs. optimization
Using the data: support of bidding mechanisms
Having the right technology platform for all of it
Is there an opportunity for incremental conversions?
32. Confidential & Proprietary
Step 1: Store GCLID upon conversion
Step 2: Predict CLV using tools like the
Google Prediction API
Step 3: Upload conversion to AdWords
using Offline Conversion Import based
on GCLID (using CSVs or API)
Step 4: AW Auto-bidding optimizes bids
based on CLV
$ - Sale or Sign-up
Prediction of CLV
A) Optimize for Lifetime Value using Offline Import
33. Confidential & Proprietary
Offline Conversion Import
1
2
Create a CSV with Conversion Value of CLV, paired to a gclid.
Try uploading the CSV
34. Confidential & Proprietary
In AdWords, you then can get a custom column of imported conversions.
It is recommended to start with a separate value, i.e. not including this metric in
Conversions.
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Target ROAS bidding strategy (simple example)
Current ROAS: 6.67 (Revenue = 1,000,000, Cost = 150,000)
Sum of CLV_12months: 350,000 (of incremental gross profit)
Expected 12 months ROAS: 9.00 (+35%, Revenue = 1,350,000, Cost = 150,000)
You can calibrate target ROAS by -35 % to 4.33 and estimate the reach of the
same or even higher revenue.
36. Confidential & Proprietary
Read more about Offline Conversion Import
https://support.google.com/adwords/answer/2998031?hl=en
and learn how to optimize it via API
https://developers.google.com/adwords/api/docs/guides/importing-conversions
More about target ROAS auto-bidding strategy
https://support.google.com/adwords/answer/6268637?hl=en
37. Confidential & Proprietary
B) Google Analytics CRM Integration
CRM Visitor
ID: 123456
Loyalty
● Lifetime Value: High, $100k
● Gender: Male
● Visited Store on 3/15/16
Male
USER ID
123456
High
Customer uploads CRM data using CRM
Visitor ID as join key via a csv file, API or
Measurement Protocol
3 Remarketing list is defined in GA based on CRM imported user attributes and exported to
Adwords/DoubleClick
Customer generates CRM Visitor ID and sends
it to GA via Custom Dimension (or utilizing
User ID) during site visit
1 2
pred_CLV High
38. Confidential & Proprietary
Act on CRM User Insights, e.g. CLV bucket
Step 1: Create user segments based on the integrated
CRM data
Step 2: Compare the performance of, i.e. loyalty-
targeted campaigns across members
Step 3: Optimize campaign targeting and bidding
Step 4: Use GA remarketing for robust CRM-linked
audiences retargeting (RLSA, GDN)
pred_CLV High
Segment: High CLV
39. Confidential & Proprietary
tl;dr
1. When you care about long-term profit,
go for the pure CLV!
2. Act on CLV by importing it into your marketing
solution and calibrating performance targets.
3. Target ROAS, RLSA and GDN remarketing are
your actionable friends.
40. Confidential & Proprietary
Additional reading
For managerial overview of CLV and Customer Equity, read Peter Fader’s book on
Customer Centricity. It is thin and recommended.
If you want to start with modeling of CLV, read Gupta’s article (PDF) and study
Bruce Hardie’s notes. For e-commerce, start with Pareto/NBD (if you use R, there
is a package Buy 'Til You Die).
Find out more about Pavel’s research project http://clvresearch.github.io/public/