Driving Better Products with Customer Intelligence


Editor's Notes

• #2: While the hyper-connected, digital world that we live in has created massive opportunities for businesses, it has also created massive risks. These business risks come in a variety of forms from emerging cyber threats that are turning IoT devices into botnet armies, to fraudsters manipulating digital assets, to ever changing compliance regulations that are trying to keep up with the changing times. We, as an industry, need to leverage technology to our advantage to lower enterprise risk and better secure our business.
• #5: With maturity of the platform and  technology ecosystem, and with enterprises better understanding not only the promise of the technology but also how to implement it, we are seeing a fundamental shift in the market….. Hadoop and big data are no longer about technologies only, nor are they  simply about cost reduction. In fact, there have been shifts towards aligning data to business objectives in order to derive even greater value out of big data. The three areas of opportunities within businesses generally are: Customer 360 - How do I understand my customers and my channel better to improve my topline? Data-driven products - How do I create better and more products to satisfy the needs of my customers? Risk - How do I make sure that the company complies to rules and regulations, protects customer and enterprise information, and minimize the risk factors?
• #7: Offer personalized product offerings or derive specific upsell/ cross-sell opportunities based on modeling a number of key attributes including - subscriber’s usage patterns, device preferences, billing data, customer support requests, purchase history, buying preferences combined with their personal information such as demographics, location and socio-economic influences. Telcos can now create targeted customer micro-segments to offer more personalized offers and campaigns. This enables CSPs to proactively present the right offer at the right time, in the right context to the right customer in order to improve conversion rates. Examples include – personalized data top-up plans or up-sell recommendations based on data usage, device upgrade campaigns based on specific customer preferences, and discounts or tailored offers based on recent purchases or enquiries or calls into the call center
• #8: Start with ingesting the “best” version of your customer profiles from a transactional system or an existing data warehouse Identify your common identifiers across datasets: customer name, number, IMEI, IMSI Enrich with additional demographic information from other systems Deliver your first use case with this information, e.g.: Lifetime value modeling, Device and plan modeling, Next device offer Continue to add datasets – such as purchase behavior - and explore common identifiers across your datasets As you explore those new datasets, enrich your customer profile with the additional information Continue to deliver additional use cases,
• #9: Lets contrast this with a flow with Enterprise Data Hub:
• #11: Key point: With the right approach, ingest can happen far more effectively and efficiently that before Sub point 1: Not everyone is a developer On one hand we’re extremely lucky: we’re in a market where there’s seemingly an endless number of choices for solving our various data problems. The tricky part is many of them are rather technical in nature, requiring developing new skills or seeking out hard to find resources (ie.personnel) to make use of them. While many folks thrive on being a hard core developer, many others do not, a lot of times simply because it’s faster to use simplified tooling in order to complete a project faster. The point here is you should not be constrained from taking advantage of new technologies if you lack the skills, and your adoption doesn’t need to take as long as it is if you don’t want it to. Sub point 2: Integrations are abundant and unnecessarily rigid
• #45: Mention that this is a Tableau report from the Vendor Reconciliation System
• #46: Mention that this is a Tableau report from the Vendor Reconciliation System