Aug
How Great Research Helps Financial Services Companies
jerry9789 0 comments Brand Surveys and Testing, Brandview World, Burning Questions
From maintaining loyalty and fostering customer relationships to focusing marketing messages on the most profit-optimal consumer, great research is helping Financial Services companies identify not only their best customers and prospects but also their needs and why they prefer their brand over others. This is done through a high-quality segmentation study and persona development, which break a company’s market into different groups so that different strategies for marketing to these groups can be leveraged. The main reason a company wants to complete market segmentation research is so they can gain actionable insights, like how to sell more of their product or services.
Take for example, Banner Bank for whom Cascade Strategies developed a brand model which identified “Strivers” as the primary segment they should focus on. The bank initiated special promotions and appeals featuring the products of greatest interest to Strivers. A Striver-specific ROI program was developed to measure the degree of program success. Modeled indices were used to set Striver product targets by branch. After 2 years of activity, Banner Bank exceeded all key Striver product targets system-wide.
Read about our approach to high-quality brand development research here.
Another example is the case of Capital One where they needed help trying to identify the “persona” or psychographic type most interested in adopting a certain mobile app for personal investing. We conducted in-person depth interviews with “mobile-minded consumers.” We also conducted an unpacking session with Capital One staff where individual staff members were given assignments to review videos and be prepared to discuss key traits and behaviors of respondents, such as outlooks, investing styles, goals, worries, needs, plans, and so forth.
We identified that the “Empath” is the most interested in adopting a certain mobile app for personal investing. The “Empath” persona is fairly immersed in pragmatic thinking and probably best understands the possibilities for “thinking” or guidance apps, allowing Capital One to focus their brand campaign effort on the needs of this psychographic type. The net result was a highly successful new product introduction.
Read about our approach to segmentation studies and the development of brand personas here.
“But wait, can’t AI do this?” you may ask. While there is a faddish and hype-driven tendency to turn quickly to AI for short-cuts in market research, AI cannot yet fully replicate the deep interpretive and intuitive skills of the human brain, especially the right brain (the nonrational side). Moreover, effective AI deployment requires human supervision and involvement as final arbiter of how the outcomes will be leveraged.
As you can see, market research results as good as the examples above come from human-centered thinking, the kind that allows brands to break past ordinary bounds and achieve true excellence. It’s this kind of extraordinary thinking that Cascade Strategies has consistently provided a long list of US and international clients for 33 years.
Feel free to reach out to us to discuss your needs at https://mktgdatascience.org/
Aug
Five Ways AI Can Help Telecom Companies Improve Their Marketing
jerry9789 0 comments artificial intelligence, Burning Questions
By moving away from business-driven marketing towards customer-centric, data-driven, and highly customized efforts, companies like telecom operators can thrive in these rapidly changing times. Here are five examples of how telecom companies can benefit from utilizing Artificial Intelligence in their marketing:
1. Increase in Product Marketing
With the millions of customer data they’ve collected, telcos can leverage AI to create targeted marketing campaigns via text, email, online ads, etc. This helps them gain a more real-time picture of their users’ experiences, thanks to sharper insights, suggestions, and trend recognition. Critical marketing knowledge and understanding of their user base are also enhanced by incorporating machine learning apps and algorithms into their product.
2. Improved Campaign Performance
Personalization as a strategy has proven through time its helpfulness in boosting several types of marketing campaigns. Integrating AI into the mix can rapidly grow its scale and capacity.
Ad targeting becomes more efficient with AI identifying the most appropriate customers for specific ads based on secured information on buying history and user preferences.
And by also automating user journeys, marketers are able to decrease the time and costs of sales targets and conversions.
3. Addressing Customer Service Issues Better
AI allows telcos to respond quickly to customer experience concerns by gathering data and identifying where the user journey fails, fostering customer satisfaction. Various AI-powered software analyzing customer feedback also improves customer support efforts by finding more appropriate, more empathetic solutions.
Front-end customer service employees can also get holistically educated about various issues and scenarios through AI training. Here the AI takes on the role of a customer. AI training also helps businesses cut back on major labor and time costs.
4. Improved Digital Marketing and Customer Engagement
Cloud-based products offer well-integrated data insights and marketing intelligence, machine learning and analytic technologies with recommendations, multi-dimensional visualizations of complex data, and free-form user analysis.
Such products solve problems by allowing users to easily integrate disparate data sources, breaking down traditional silos and enabling insight-driven decision-making.
5. Notifications Sent at More Appropriate Times
AI is also being used to boost push campaign engagement by determining the best time of day to send notifications to consumers, preferably the time they are most open to brand interactions.
With the enormous data and complexities handled in industries, telcos must use AI in staying ahead of competitors. It’s just simpler to address problems and automate solutions, run daily operations more efficiently, and provide better customer service and satisfaction. In the long run, telcos continuing their development along this path are more likely to emerge as undisputed winners.
Mar
What if every US citizen had a dollar for every good decision made by the president and lost a dollar for every bad decision? How much would Americans have in their “Decision Account” now? What about a half-good decision? Would Americans’ Decision Account be credited for 50 cents? Clearly, the whole matter hinges on what is defined as a good or bad decision.
Mar
Responsible AI – What Causes Bias in Training Data?
jerry9789 0 comments artificial intelligence, Burning Questions
Over the past few decades, the use of AI in business has grown tremendously. By 2030, AI may generate up to $15.7 trillion in revenue to the global economy.
From process automation to sales forecast, the potential applications for AI in business are nearly limitless. But, you’ve still got to wonder, what happens when we place so much power on fairly new technology? Will it be fair or biased? Will it try to take over the world in the future? We don’t give the fear mongers much weight about AI taking over the world, but unchecked bias in AI data or models can lead to unintended negative consequences that do real harm.
Mar
Artificial Intelligence (AI) is becoming a critical component of digital marketing. AI in marketing can be particularly revelatory, often delivering valuable insights that marketers can use to develop personalized content, drive conversions, and improve customer experience. Such insights help develop effective marketing strategies, which increase Return on Investment (ROI) for AI implementations.
Mar
4 Ways Data Can Help Create Sustainable Revenue Growth
There is no question that year after year, the cost of revenue (COR) generation continues to climb. Look at publicly traded companies in nearly any sector and read the reported costs associated with sales and marketing. In almost every case, the costs of acquiring revenues continue to outpace the gross revenues generated. It costs more to make the same money. In today’s world of shifting digital and economic landscapes, tapping into data in real time and extruding insights gives executives a critical tool to stay ahead of the curve. Near real-time decision making is a necessity – not a luxury.
Feb
Data Science Team: Build or Rent?
Eric Layland 0 comments artificial intelligence, Burning Questions
Building an Efficient & Effective Data Science Team
There are numerous reasons why a company may decide to develop a data science team in their organization. The skills an in-house team brings can enable organizations to turn raw data into strategic assets. Their skills lead to better use of data assets including understanding customer behavior, error detection, automation of repetitive tasks, and overall more sophisticated decision support. A data-driven organization can benefit and gain a competitive edge.
However, building an effective and efficient data science team is not as simple as adding new hires. Before we can discuss whether to rent or build a team of experts, it’s essential to understand the roles typically needed to fully staff a data science team.
The included salary estimates do not include benefits. The figures are an average of the latest available data from Salary.com, PayScale and ZipRecruiter and reflect US labor markets.
Feb
Marketing AI Curious? Here’s 7 Key Questions to Ask
jerry9789 0 comments artificial intelligence, Burning Questions
Artificial Intelligence(AI) has recently been integrated into marketing and is still in its early stages. It makes automated decisions based on available data and audience observations or economic trends that impact marketing. By doing so, it enables marketers to gain more insight and understanding of their target audiences.
However, a business must comprehend how AI Marketing works and its effects before adopting it. Here are seven questions every company interested in AI Marketing should ask themselves.
Feb
“Data Scientist in Residence”, “Chief Data Officer”, “Big data engineer”…the data science buzzword du jour is “Data Scientist.” These data scientists are part data analyst, part statistician and part software developer. With data quickly becoming a top strategic business priority for many companies, the need for data scientists will only increase – especially as we move toward an ever more data-driven world.
If data represents a strategic asset for your company, then you should be wondering if a data science team is needed and is it better to buy or rent the talent? Data analysis can be done by anyone with analytical skills, right? Well, the functions of a data scientist on a data science team are broader than initially meets the eye….and they typically need to work closely with data analysts and subject matter experts.
Data Scientists are in demand, and the salaries for US-based professionals can easily reach six-figure levels (about $120K + benefits according to Indeed). The number of data science jobs is expected to grow by 24% over the next five years. But do you really need a team of data scientists?
Jan
At The Core of Marketing Decision Making: Advanced Analytics
jerry9789 0 comments artificial intelligence, Burning Questions
Advanced Analytics is an encompassing term that is used to categorize techniques and technologies that seek to understand what happened in detail or to predict what may happen with an unmatched degree of precision. We use the term to encompass services that include Data Science, Artificial Intelligence, or AI and related technologies. The field of AI-powered Advanced Analytics draws on various aspects of neuroscience, statistics, mathematics, and computer science. But perhaps more critically, it is heavily influenced by the disciplines of philosophy and psychology to understand human motivations.
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