Module 1 Information Management and Analytics Final

Editor's Notes

• #15: Data wasters. These companies underperform financially, and their business and IT functions are not aligned. They collect data, but severely underuse them. Found in every industry, these companies are most likely to put a mid-level manager in charge of their data strategy.* Data collectors. These companies are submerged in data. They recognise the importance of data, but lack the resources to do anything about them, beyond storing them. They suffer from poor IT/business alignment, with nearly one-quarter maintaining that IT does not understand the importance of data; another quarter says the same of the business side. Companies in the healthcare and professional services industries are likely to be found in this category* Aspiring data managers. These companies have fully embraced the importance of big data to the future of their company. They allow data to inform strategic decisions, and invest in them aggressively. But they still lag behind the leaders. Sixty-six percent of them put only about one-half of their data to good use. Companies in the communications and retail industries are most likely to be found in this category.* Strategic data managers. This is the most advanced group of big data managers, with the most mature capabilities. Fifty-three percent of these strategic data managers say they outperformed their peers in the last fiscal year, 44% say they are on even par and only 1% say they underperformed. They are most likely to be found among manufacturing, financial services or technology companies. Strategic data managers first identify specific measurements and data points that align closely with corporate strategic goals.
• #67: Tie back to IMM and foreshadow the predictive modeling, segmentation & SNA work
• #69: Customer and product profitability mutually depend on each other, i.e. two customers having exactly the same product and services package may differ heavily with their profitability, also the same product sold to two different customers may cost the operator differentlyTwo flat-access-fee product users may demonstrate different attitude to the available basket of services and generate highly different product costs; Two customers generating similar revenue may utilize different services bundles;Customer, product and service profitability are not universal and transferable across the entire database; more granular profitability calculator is necessary to propose right product to right customer micro-segments
• #72: Which customers are profitable?Those who keep generate positive Gross Profit*/ Net Profit ** month-after-monthThose, who’s cumulative Gross Profit/ Net Profit is already greater then Acquisition Costs (SAC) and Retention Costs (SRC)* Gross Profit (Return On Sales) = Gross Revenues from Services – Costs of Goods & Services Sold + Revenues from Interconnect and Interworking connections and messaging**Net Profit = Gross Profit – Costs to Serve (call center calls, claims, HLR & Network Costs, etc. directly related to customer activities and services used)
• #73: Which customers are profitable?Those who keep generate positive Gross Profit*/ Net Profit ** month-after-monthThose, who’s cumulative Gross Profit/ Net Profit is already greater then Acquisition Costs (SAC) and Retention Costs (SRC)* Gross Profit (Return On Sales) = Gross Revenues from Services – Costs of Goods & Services Sold + Revenues from Interconnect and Interworking connections and messaging**Net Profit = Gross Profit – Costs to Serve (call center calls, claims, HLR & Network Costs, etc. directly related to customer activities and services used)
• #74: Which customers are profitable?Those who keep generate positive Gross Profit*/ Net Profit ** month-after-monthThose, who’s cumulative Gross Profit/ Net Profit is already greater then Acquisition Costs (SAC) and Retention Costs (SRC)* Gross Profit (Return On Sales) = Gross Revenues from Services – Costs of Goods & Services Sold + Revenues from Interconnect and Interworking connections and messaging**Net Profit = Gross Profit – Costs to Serve (call center calls, claims, HLR & Network Costs, etc. directly related to customer activities and services used)
• #75: Which customers are profitable?Those who keep generate positive Gross Profit*/ Net Profit ** month-after-monthThose, who’s cumulative Gross Profit/ Net Profit is already greater then Acquisition Costs (SAC) and Retention Costs (SRC)* Gross Profit (Return On Sales) = Gross Revenues from Services – Costs of Goods & Services Sold + Revenues from Interconnect and Interworking connections and messaging**Net Profit = Gross Profit – Costs to Serve (call center calls, claims, HLR & Network Costs, etc. directly related to customer activities and services used)
• #76: Which customers are profitable?Those who keep generate positive Gross Profit*/ Net Profit ** month-after-monthThose, who’s cumulative Gross Profit/ Net Profit is already greater then Acquisition Costs (SAC) and Retention Costs (SRC)* Gross Profit (Return On Sales) = Gross Revenues from Services – Costs of Goods & Services Sold + Revenues from Interconnect and Interworking connections and messaging**Net Profit = Gross Profit – Costs to Serve (call center calls, claims, HLR & Network Costs, etc. directly related to customer activities and services used)
• #85: Social Network Propensity Score - using centrality and the network structure we can generate highly predictive propensity scores.These propensity scores can be for customer actions such as churn, acquisition, prepaid to postpaid migration etc.Persistent Individual Identification- using links and calling pattern mechanisms to assign similarity scores to individuals. We can track individuals over time, even through number or address changes.The assumption/requirement is that they continue to talk to the same people/telephone numbers over time.Customer, Household, and Life-Stage Segmentation.- Using community detection, in addition to demographics (age, gender etc), location, and address information where available we can allocate customers into family segments.Customer Value - An accurate metric of value is also a product of your influence upon others. If a low value customer is highly connected and a great customer advocate they may be responsible for significant acquisition of many customers (whom may be high value) and reduces churn, and hence marketing costs for retention.Acquisition Of High ARPU Prospects - Refer-a-friend and ‘member-get-member’ offers often yield better results when you are aware of the $ value of off-network friends and the potential market share (number of off-network friends) each customer can bring.Agile Campaigns- By having customer link analytics prepared, it can be matched daily to recent churners. The next day (or even hourly) the friends or any churned customers can be contacted to prevent viral churn.