Marketing technology landscape

This visual graphic is very useful for me.  Technology impacts hugely on marketing activities, this article gives me an answer of how much influence and how many tools reshape the marketing activities.

I keep it on my blog. Once I need it, this graph can give me many inspirations on marketing.  I use some marketing tools, but it looks there are over 5000 tools.

" This platformization of marketing is that marketers are able to more easily build best-of-breed marketing stacks. Instead of choosing suite or best-of-breed, many marketers are now taking a suite and best-of-breed approach — using the suites as digital marketing hubs and then augmenting them with a range of more specialized products to bake their own, special marketing and customer experience cake."

marketing_technology_landscape_2017_slide.jpg

廣告

15 social media managment tools

I’ve used some of those 15 tools.  It’s useful.

Employees’ behavior on branding

//platform.twitter.com/widgets.js

品牌就是員工的那張嘴, 品牌就是企業如何對待員工.

Tips of Marketing metrics

MaxthonSnap20170418104120

Power on the market

A network good.

Sales volume

“Value"

Experiment, test, try

customers= asset

好的公司, 怎麼用都是對的,

歪的企業, 怎麼看都不通

 

Twitter 技巧

工具關鍵是在人,  善用工具, 組織猶如數位神經一樣靈敏. 員工願不願意分享, 關鍵還是在人, 組織設計用心與否關鍵還是在人,人對了, 心正了,目標清楚了,  知識, 工具, 各種機會就是在那裡, 看懂, 實踐,應用, 分享, 會用的就是會用, 公司加快了效率, 提生了生產力. 好公司都是這樣的.

 

MaxthonSnap20170318122323

Amazon Marketplace Web Service (Amazon MWS)

  • 亚马逊商城网络服务 (Amazon MWS)

an integrated Web service API that helps Amazon sellers to programmatically exchange data on listings, orders, payments, reports, and more. XML data integration with Amazon enables higher levels of selling automation, which helps sellers grow their business. By using Amazon MWS, sellers can increase selling efficiency, reduce labor requirements, and improve response time to customers.

(Reference: https://developer.amazonservices.com/)

(Reference: https://developer.amazonservices.com.cn/)

Machine Learning for Marketing

The marketing big data ecosystem being impacted by machine learning in four major areas:

  1. Automated data visualization (including ML results) will become more rich, and user-friendly.
  2. Content analysis (textual, lexical, multimedia/rich) will be used to drive better marketing conversations.
  3. Incremental ML techniques will become more prevalent, leading to real-time, not just on-going and automated, changes in marketing execution.
  4. Learning from ML results will accelerate the growth and skills of marketing professionals.
  • Automated Data Visualization tools: Tableau and Qlikview

Predictive model : The objective of ML is to build predictive model for forecast.

the ability to modify a solution that is already in place by introducing new data rather than having to stop using the current solution before building a new model from scratch.

(Source from How Machine Learning Will Be Used For Marketing In 2017)

推薦系統

另一篇po文 at Recommendation system

 

E-commerce Recommender System

推薦人系統.

推薦是基於關聯, 內容, demographic profile, 用戶的產品評價,評價相近的用戶

還有,多交些印度朋友吧

“Right product  is to the right people at the right time"

Personalization, Lock in, Behavior targeting

“know your customer"

" accurate"

  • Building Better Recommendation Engines

“Content is King" 到底是什麼意思?

這句話是Bill Gates 1996 時說的.

“Content is where I expect much of the real money will be made on the Internet, just as it was in broadcasting.”

所以網路上,當內容被傳播, 是可以靠內容賺錢.  當時1996, 現在讀很正常.
現在應該進一步研究: 倒底“什麼內容"或是"內容裡有什麼" 是能賺錢 ?

好的內容幫助行銷, 行銷也幫助內容被更多人接受.  內容本身的內涵與讀者,觀眾之間的關聯必須要理解

內容行銷:

  • Increasing visibility.
  • Encouraging backlinks for SEO, and social shares.
  • Optimising the website for long tail keywords that are harder to target through the
  • website’s static pages.
  • Generating new customers, or clients, or whatever your end goal is (hopefully).

好的內容能增加流量,對於搜尋和分享有助益, 內容中的關鍵字, 幫助搜尋, 有助尋找新客戶或粉絲.

“內容裡關鍵字的精準" 影響內容被搜尋到的程度.
因此,內容會變得更競爭, 很多內容關鍵字會是一樣的.
所以 內容要時時更新和相關. 好的內容行銷策略能提升網站流量, 增加客戶.

內容行銷需相當程度的客製化, 必須區隔清楚, 定位準確, 追求客戶忠誠度與粉絲經濟.
為了這一群死忠用戶, 產品加值並創造新的商機.

內容行銷原理是如此,  執行要練到很厲害,很精準,超熟練,很靈活,會調整. 多練習, 跟著數據調整, 很多行業都廣泛運用,但內容製作本身(創作者)也應該深度理解:

  • 內容的"含金量",是什麼 以吸引特定消費群
  • 內容裡的關鍵字是什麼?
  • 關鍵字精準的程度?

題材(主題), 故事, 情節, 對話, 文字, 對白…等等成為關鍵, 被搜尋到,被大數據認可的程度.

這方面的內容 各行各業差異就很大了.
有的行業很好做, 有的行業怎麼做都無效,  客戶根本就不吃這一套. 看行業,和內容屬性.要試一試,測一下效果.  這其中操作策略細節很多,不同國家又不一樣, 內容在地化和修辭的調整有很多的微妙之處.

內容製作者要深刻理解自己產出內容的品質, 能與內容行銷相輔相成.
在這些原理相通的前提下, 內容才是王.

但真正的現實是: (note1)

絕大多數的公司所面臨的一個最大的挑戰:

在網上進行內容行銷的時候,必須堅持下去,堅持到發佈的內容可以成為搜尋資料庫,而訂閱者的數量多到足夠將多年的投資變現. 內容行銷非常辛苦,需要持續不斷地更新發佈內容,知道有一天看到自己的文章瀏覽量終於有了起色,最後終於看到這個渠道帶來了可觀的潛在使用者數量,能這麼做的公司很少。 但是這樣的模式確實有用,能夠堅持下來的公司都能嘗到甜頭,他們不僅僅享受到激增的流量和潛在使用者的增長,他們能夠獲得一個可以預期,可實現規模化的渠道,能夠幫助公司以前所未有的速度成長.

(Ref1: http://www.silkstream.net/blog/2014/07/content-is-king-bill-gates-1996.html)
(Ref2: https://scrunch.com/blog/5-reasons-why-content-is-king/)

(note1: http://www.inside.com.tw/2016/05/15/why-medium-works)

 

%d 位部落客按了讚: