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Isnʼt Retention the Value Proposition for Data Analytics? Based upon recent meetings w/ LoBs @ LDS , Zappos , UMC , Allegiant Air , Swedbank 1. What are customers thinking? 2. What trends compel them? 3. What do they want from IBM? 4. Examples that interest them Christopher Perrien Internet Technologies [email protected] mobile: 919.949.1145 Not low-cost provider, must be fast 2 market Necessitates innovation across entire value chain Requires interconnection of people & systems Why Smarter Planet & Industry Align. & Analytics Can explain IBMʼs portfolio composition presentation design: Blue Pane Studio We believe that the emerging capabilities of Internet related technologies can improve how we work and the way that we live. Our goal is to enhance IBMʼs software portfolio based upon hands- on projects with our clients.

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Isnʼt Retention the Value Proposition for Data Analytics? Based upon recent meetings w/ LoBs @ LDS, Zappos, UMC, Allegiant Air, Swedbank

1. What are customers thinking?

2. What trends compel them?

3. What do they want from IBM?

4. Examples that interest them

Christopher Perrien

Internet Technologies

[email protected]

mobile: 919.949.1145

Not low-cost provider, must be fast 2 market

Necessitates innovation across entire value chain

Requires interconnection of people & systems

Why Smarter Planet & Industry Align. & Analytics

Can explain IBMʼs portfolio composition

presentation design: Blue Pane Studio

We believe that the emerging capabilities of Internet related technologies can improve how we work and the way that we live. Our goal is to enhance IBMʼs software portfolio based upon hands-on projects with our clients.

What are Customers Thinking?

Uncertainty & Instability characterize many markets.

Trust & Accountability is at premium.

Cost Control & Rapid ROI prevail.

What are Customers Thinking II?In addition, new ways of working, socializing and collaborating

are rapidly evolving which dissolve the Brandʼs familiar patterns of engaging its audience. Prospective customers have many choices making new customer acquisition nearly prohibitively

expensive in the current economic climate.

What Trends Compel Them?

The widespread adoption of Twitter (75mm) and Facebook (400mm) in conjunction with the location

awareness capabilities of new forms of mobile devicespromise improved methods for understanding and

communicating with customers. How can these tools better enable customer - and employee - dialogue and,

retention?

What do they want from IBM?

Customers agree that there is much useful information in text files or other sorts of notes / unstructured data in the call center or from an

individual practitioner.

Is there a way to effectively identify members looking for similar kinds of employment beyond the broadest job classifications?

Is there a way to identify like-minded travelers beyond destination, i.e. business travel or vacation travel? Can an airline site easily

affiliate members the way that Facebook does?

How might text analytics improve the return on investment of Stimulus Funds in Electronic Medical Records?

How can we identify the brands of products that customers might look for but cannot find in our inventories (sold Adidas and they

searched for Yonex tennis shoes)?

Have 10mm account holders and 1mm small businesses. How can these be segmented beyond traditional financial product

classifications?

What Examples Interest Them?

Vancity is Canadaʼs largest credit union with a strong voice and a deep sense of

social commitment.

IKEA, renown for its affordable and clever designs, is in its 3rd year of Small

Business consulting seminars.

USAA achieves #1 customer service rankings without a branch banking

infrastructure.

Getting Started with IBM

The Smarter Planet theme is especially effective in explaining why IBM goes to market

as it does.

C-Level Executives are interested in the process of Jams & Think Place & TAP.

Sr. Marketing Executives are intrigued by the prospects of text analytics and ask “How has

IBM applied to its customers?”

IT executives are attracted to the capability of converting unstructured text to structured for

familiar data analysis & reuse.

Connections, especially Profiles and Expert Resource Locator, are compelling ways of

getting started.

Banter (customer sentiment analysis) and BlueWork (mobility API layer) were well

received ISL briefings.

Helpful would be a comparison of the interrelated products.

StatisticsTextMining

DataMining