What You Need to Know
- Breakouts in the Customer Engagement predictive analytics are Customer experience, Customer loyalty program, Brand loyalty. Seriously consider these technologies to gain a strategic advantage.
- The technologies who are at the peak of their interest are Customer experience, UserEngage, Vlogging.
- By far most employment needs are found in the Customer experience, Customer relationship management, Brand loyalty technologies.
- These 3 fields have the most active practitioners who have the specific skill set or experience: Customer experience, Customer relationship management, Internet marketing.
- Wayback Machine, LiveChat, Customer relationship management lead in searches for information online.
- These three technologies are receiving the highest investments to gain clients: Help Desk Software, Customer Relationship Management Software, Customer Service Software.
- These three technologies have the most active advertisers: Internet marketing, Customer Relationship Management Software, Customer Loyalty Software.
- In patents, these three technologies have the most coverage Optinize, Customer relationship management, User generated content.
- The most publications are available for Business communication, Internet marketing, Target market.
- Instruction and courseware availability is highest in these technologies: Vlogging, Internet marketing, Optinize.
- By arranging Customer Engagement related applications and technologies thematically, Blokdijk’s classic clarifies all the principles of Customer Engagement’s potential of business and investing.
- Blokdijk’s new report, the Customer Engagement Predictive Analytics Report, takes deep dives with Customer Engagement topics inside their potential to glimpse the future.
The Customer Engagement report evaluates technologies and applications in terms of their business impact, adoption rate and maturity level to help users decide where and when to invest.
Customer engagement (CE) is an effect, a reaction, a connection, a response and/or an experience of customers with one another, with a company or a brand. The initiative for engagement can be either consumer- or company-led and the medium of engagement can be on or offline.
The Predictive Analytics Scores below – ordered on Forecasted Future Needs and Demand from High to Low – shows you Customer Engagement’s Predictive Analysis. The link takes you to a corresponding product in The Art of Service’s store to get started.
The Art of Service’s predictive model results enable businesses to discover and apply the most profitable technologies and applications, attracting the most profitable customers, and therefore helping maximize value from their investments. The Predictive Analytics algorithm evaluates and scores technologies and applications.
The platform monitors over ten thousand technologies and applications for months, looking for interest swings in a topic, concept, technology or application, not just a count of mentions. It then makes forecasts about the velocity of the interest over time, with peaks representing it breaking into the mainstream. Data sources include trend data, employment data, employee skills data, and signals like advertising spent, advertisers, search-counts, Instruction and courseware available activity, patents, and books published.
Predictive Analytics Scores:
001325 – Customer experience
000378 – Customer loyalty program
000225 – Brand loyalty
000220 – Touchpoint
000161 – Customer Service Software
000125 – Customer Thermometer
000115 – Voice of the Customer
000108 – Totango
000108 – Engagement marketing
000088 – Customer Relationship Management Software
000080 – Target market
000076 – Get Satisfaction
000067 – Online community
000067 – LiveChat
000060 – User generated content
000058 – UserVoice
000055 – Conversion (marketing)
000052 – Call Center Software
000051 – Wayback Machine
000050 – Business communication
000046 – Live Chat Software
000043 – Executive sponsor
000041 – Journey Sales
000036 – BoldChat
000033 – Customer relationship management
000029 – Woobox
000017 – Vlogging
000017 – LoadStorm
000015 – SAS Customer Intelligence
000015 – Click-through rate
000014 – CustomerMatrix
000011 – Internet marketing
000008 – Engagor
000006 – Social phenomenon
000003 – Multichannel retailing
000002 – The Long Tail
000000 – UserEngage
000000 – The Customer Factor
000000 – Stakeholder theory
000000 – Simmons Research
000000 – Podcasting
000000 – Optinize
000000 – Map My Customers
000000 – Help Desk Software
000000 – Employee Engagement Software
000000 – Digital object identifier
000000 – CVP Analysis
000000 – Customer Satisfaction Software
000000 – Customer Loyalty Software
000000 – Customer Experience Software
000000 – Customer Engagement Software
000000 – Contact Management Software
000000 – Complaint Management Software
000000 – Acromobile