Hello Mobile marketing

22

Draft about mobile marketing, digital discipline (transformation)

+ Netflix digital transformation, Nike, Coke use-case, bank fintech use-case
+ Cloud (virtualization), big data (6v model), social, mobile, things

Digital marketing > Mobile marketing >
Adbrix (Attribution Adhoc Analytics Audience Smart Pattern) , Tune, Vizury, etc

Mobile Index, Campaign Intelligence, LiveOperation, Tradingworks

Books:

Engaging Customers Using Big Data : How Marketing Analytics Are Transforming Business.

Data is transforming how and where we market to our customers. Using a series of case studies from pioneers, this book will describe how each marketing function is undergoing fundamental changes, and provides practical guidance about how companies can learn the tools and techniques to take advantage of marketing analytics.

Statistical Modeling and Analysis for Database Marketing : Effective Techniques for Mining Big Data

Digital Disciplines: Attaining Market Leadership via the Cloud, Big Data, Social, Mobile, and the Internet of Things

Predictive Marketing: Easy Ways Every Marketer Can Use Customer Analytics and Big Data (Tools and Algorithm)

While predictive marketing uses predictive analytics under the hood, you do not need to know predictive analytics at all to be a predictive marketing expert. There is a huge career opportunity that comes from being an early adopter of new technologies, like predictive analytics, and new business practices, like predictive marketing. The most important thing is to demonstrate curiosity and ask the right questions about your business and customers. Management is starting to look to marketing to inform major strategic decisions for the company. This type of visibility in the company can be great for your career. Successful marketers learn to combine the science of numbers with the art of creativity. Using data, you can discover new customer personas and marketing strategies and test that your creative ideas are working.

Predictive models will become more easily accessible and available to all marketers, at companies large and small, as time goes on. The authors believe the widespread accessibility of big data and machine learning will spurn a true culture shift of rebuilding marketing practices around the customer, rather than around products or selling channels. This chapter discusses some of the predictive models which advanced marketers could use. An engagement propensity model predicts the likelihood of a customer to engage with a brand. A total size of wallet model can predict the maximum possible spend for each customer. A pricing optimization model predicts the price that best drives sales, volume, or profitability. A keyword‐to‐contact recommendation model can predict the affinity of a customer to certain content. A predictive clustering model predicts which cluster a customer will fall into in the future.

Mobile Marketing : How Mobile Technology Is Revolutionizing Marketing, Communications and Advertising

Link about Google analytics vs Firebase

https://www.bounteous.com/insights/2018/02/20/choosing-firebase-google-analytics-sdks-app-tracking/

How ad-hoc (on demand) reporting can be done on Big Data? User should be able to drag and drop fields just like in any BI tool.

Ad-hoc near real-time reporting is possible with special distributed analytic databases + BI tool that can connect to it and query like ROLAP (on-the-fly). Some popular solutions:

  • Cloud: Amazon Redshift with compute nodes (SSD volumes) can show acceptable response time (in seconds)
  • Commercial: Vertica (fast but expensive)
  • Free: Yandex ClickHouse (open source) is very fast and offers ultimate performance, but has some limitations: data cannot be updated/deleted, limited support of JOINs – huge flat table is much better
  • NoSQL: MongoDb, ElasticSearch: in some cases they can be used as analytics database too, for not-very-big-data (also no JOINs)
  • In-memory real-time analytics databases like MemSql (needs a lot of nodes for handling big data)
  • Specialized GPU-based solutions like MapD (require servers with expensive graphics)

Regarding BI tool for ad-hoc reporting: this might be even PowerQuery. If you are looking for web-based report builder you can check our online tool for pivot tables and pivot charts: seektable.com (it can connect to Redshift, MemSql, ClickHouse, MongoDb, ElasticSearch)