The Top 10 Questions Every Brand Must Answer To Grow In 2015

Every marketeer faces a dizzying array of choices in terms of strategy, tactics, and tools through which to reach their customers and inspire them to buy your products. As the media landscape becomes more fractured and the tools more varied, it’s more important than ever to stay focused on the right priorities that will ensure short-term and long-term success. With that in mind here are the top ten questions every brand must answer if they hope to grow in 2015.

1. What is your brand’s purpose? Every marketer is now aware that Boomers, Millennials, and Gen Z generations are looking to brands to be more responsible in exchange for their product purposes. As such, a clear definition of your company purpose is critical to capturing their attention and converting their support to sales.

2. What is your brands story? Once you have defined your brand’s purpose, mission, and vision you need to be able to distil that into a brand story that employees and customers want to share. Only then will you unlock the power of social technologies to amplify your message and build your customer community.

3. How do you align your leadership, employees, and partners around that brand story? Too often marketers think only in terms of how they will share their story with customers and ignore the need to create a company culture that is in alignment with that story.

4. How do you align your corporate citizenship, sustainability and foundation efforts? For decades each one of these areas had been treated as distinct silos within a company matrix. As such, they are often insufficiently connected or aligned with a brand’s story. Only when they are all pointed in the same direction can they amplify one another to generate marketing efficiencies that improve your bottom line.

5. How do you align your company and product brand stories? Many corporate brands have chosen to remain effectively unknown and lead with their product brands. With the new demands for transparency and accountability, company brands are now rising to the challenge of defining their story and aligning their product brands within it.

The Top 10 Questions Every Brand Must Answer to Grow in 2015

6. How do you align your external marketing with your internal culture?There is nothing more destructive to a business than for a customer to discover that a brand’s marketing is very different to the customer’s experience. By extension, very easy for an employee to become disillusioned when they see that a brand is telling its customers one thing when their experience inside the company is another.

7. What strategies must you use to tell your story effectively using social technologies? Too often brands bring a broadcast and self-directed mentality to social tools that turn on dialogue, interaction, and intimacy. It’s not surprising then that they find that their employees’ time and marketing spend is wasted.

8. How must you use each social media channel to capture the attention of existing and new customers? Each channel presents a unique way to command the attention of different audiences and to inspire them to amplify the company’s brand story. Only with clear communication architecture can that story and these channels be sufficiently aligned to build the brand and its business.

9. How do you share that brands story effectively at a local level? The people closest to a community are the ones best qualified to share a story. As such, every brand faces the challenge of localizing its overarching story in a way that makes it meaningful and relevant to customers in order to win their attention and purchasing preference.

10. How do you establish your leadership at a global level? Irrespective of your company size, you can now lead a global conversation once you have clearly articulated your point of view on a given cultural conversation related to your products and their benefits. Any ambition smaller than that undervalues the reach and impact of the web, social media, and mobile phones.

Each one of these questions is important in their own right, but taken together they are critical for the short and long-term success of a brand in today’s social business marketplace.

Predictive Analytics Most Used To Gain Customer Insight

Using analytics to better understand customer satisfaction, profitability, retention and churn while increasing cross-sell and up-sell are the most dominant uses of cloud-based analytics today, following the results of a recent study.

Key takeaways of the study results include the following:

  • Customer Analytics (72%), followed by supply chain, business optimization, marketing optimization (57%), risk and fraud (52%), and marketing (58%) are the areas in which respondents reported the strongest interest.
  • When the customer analytics responses were analyzed in greater depth they showed most interest in customer satisfaction (50%) followed by customer profitability (34%), customer retention/churn (32%), customer management(30%), and cross-sell/up-sell (26%).
  • Adoption was increasingly widespread and growing, with over 90% of respondents reporting that they expected to deploy one or more type of predictive analytics in the cloud solution.
  • Industries with the most impact from predictive analytics include retail (13% more than average), Financial Services (12%) and hardware/software (4%). Lagging industries include health care delivery (-9%), insurance -11%) and (surprisingly) telecommunications (-33%).  The following graphic illustrates the relative impact of cloud-based predictive analytics applications by industry.

Adoption of Cloud-based Predictive Analytics by Industry

 

  • The most widespread analytics scenarios include prepackaged solutions (52%), cloud-based analytics modeling (47%) and cloud-based analytic embedding of applications (46%).  Comparing the 2011 and 2013 surveys showed significant gains in all three categories, with the greatest being in the area of cloud-based analytic modeling.  This category increased from 51% in 2011 to 75% in 2013, making it the most likely analytics application respondents are going to implement this year.

Comparison of Analytics Applications Most Likely To Deploy, 2011 versus 2013

  • 63% of respondents report that when predictive analytics are tightly integrated into operations using Decision Management, enterprises have the intelligence they need to transform their businesses.

Impact of Predictive Analytics Integration Across The Enterprise

 

  • Data security and privacy (61%) followed by regulatory compliance (50%) are the two most significant concerns respondent companies have regarding predictive analytics adoption in their companies.  Compliance has increased as a concern significantly since 2011, probably as more financial services firms are adopting cloud computing for mainstream business strategies.

Concerns of Enterprises Who Are Using Cloud-based Predictive Analytics Today

 

  • Internal cloud deployments (41%) are the most common approach to implementing central cloud platforms, followed by managed vendor clouds (23% and hybrid clouds (23%). Private and managed clouds continue to grow as preferred platforms for cloud-based analytics, as respondents seek greater security and stability of their applications.  The continued adoption of private and managed clouds are a direct result of respondents’ concerns regarding data security, stability, reliability and redundancy.

Approach To Cloud Deployment

  • The study concludes that structured data is the most prevalent type of data, followed by third party data and unstructured data.
  • While there was no widespread impact on results from Big Data, predictive analytics cloud deployments that have a Big Data component are more likely to contribute to a transformative impact on their organizations’ performance.  Similarly those with more experience deploying predictive analytics in the cloud were more likely to use Big Data.
  • In those predictive analytics cloud deployments already operating or having an impact, social media data from the cloud, voice or other audio data, and image or video data were all much more broadly used as the following graphic illustrates.

Which Data Types Deliver The Most Positive Impact In A Big Data Context