Sales

More Universities Need to Teach Sales 

這是HBR 2016 的一篇文. 很多企業對 Sales 的觀念就錯了, 學校裡也不教 “Sales",所以有點成為一個管理的漏洞. 以前台灣的大公司怎麼做生意? 受不了, 想想真是離譜又真實, 現今很多高管還是有那種60-70年代台灣的業務做生意的觀念,要會辨別.

我之前也寫過一篇關於業務的性質 , 這篇更多補充, 可以修正很多舊的偏見.

“Salespeople must work across their firms’ functional boundaries, and, depending upon the buying process, with multiple people and functions at clients" -所以Sale 像是PM, 把公司各部門串起來.

“Selling is preoccupied with the seller’s need to convert his product into cash"

Marketing with the idea of satisfying the needs of the customer by means of the product and the whole cluster of things associated with creating, delivering, and finally consuming it.”

數位化後,  Selling is increasingly a research-based activity"

更需 “business-acumen and analytical selling skills"

會做商業分析Sales是非常厲害的, 會混用多商業工具,比率,指標, 理論, 新方法,新技術.

 

 

廣告

業務是職務還是人格特質?

業務員的特質是什麼?

一種天生的特質

對客戶的同理心"的個性,能克服客戶購買前的猶豫不決

一種“介於同理心和自我驅動之間的動態狀態"

有時處處為客戶著想, 解決問題有時又非常主動,自動自發,找客戶,找出客戶的問題

兩種特質互相強化,也互相平衡.

業務員具有內在的人際關係感.
這種特質比較隱性, 看不太出來.

“對客戶的需求和反應有感覺"

人就是個性,行為,態度, 能力的交互影響.

如果把業務定義為一種職位, 但卻沒有這樣同理心的軟性人格特質, 結果會如何?

人格特質測驗, 看看有沒有這樣的"個性傾向或興趣", 而不是能力.

有這種特質,往業務方向發展會比較順利. “能感覺別人"是一種特質

雖不同領域的業務, 專業知識皆不同,

但這種傑出業務的人格特質是相同.

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

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

 

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