Social Communities

Social Communities

Social Communities

Social Communities

3 Reasons Why They’re the Best New Research Method
Introduction

Social communities are market research’s best-kept secret. They allow researchers to tap into natural avenues for communication where people are comfortable: social media.

As a result, consumers are incredibly engaged and eager to offer up rich insight. In a world where emerging CPG
companies are disrupting the industry with their ability to hit

the pavement, learn from consumers quickly, and react strategically, social communities are invaluable.

They give big companies the opportunity to be agile. Not sold yet? Great, we’re going to explore three big reasons why they’re the best new research methodology you’ve never heard of:

Social communities are powerful because they are already ingrained in consumers’ lives (think: Twitter, Facebook, Instagram). They’re also painless for participants (unlike traditional communities which require significant behavioral change).

We’ve heard time and time again how much consumers enjoy participating to the point where they are sad to see their community end. Traditional research methods like focus groups, in-home ethnographies, and in-store research, on the other hand, are more arduous for consumers because they require a substantial time commitment (usually in the middle of the day) and take place in artificial environments.

These methods help marketers understand general usage and shopping patterns, but they do not provide the same sense of authentic interaction as social communities. They are planned interviews, no matter how much you emphasize that they should reflect consumers’ “typical behaviors.”

Social communities yield insights that ultimately drive innovation, inform consumer messaging, and help refine shopper strategy.

Take a fictional case of a toothpaste manufacturer, for example. In our scenario, the toothpaste manufacturer leverages social communities to generate a breadth of insights related to the areas above (innovation, consumer messaging, and shopper strategy.) The company’s marketers are able to pick out the best insights and use them as the foundation for action.

Example: Toothpaste Manufacturer

You might be wondering: “If social communities are so great, why don’t we hear more about them in CPG?” The big reason is that they are labor intensive. They take a lot of time to facilitate, require a flexible research plan, and often necessitate extra buy-in from key stakeholders.

Despite the added effort, however, researchers who go the extra mile LOVE social communities because they elevate their qualitative insights. If you are hungering to foster an authentic connection with consumers and generate new, rich insights, you should consider them too.

Researchers LOVE social communities…and you will too!

“At the beginning, I thought ‘boy, this is going to be a long process.’ Now all I’m thinking about is how worth it communities are.”

“I never thought we could get such great data from social media.”

“This is truly a frontier in market research. In all my time in Insights, I’ve not seen qualitative learning this robust.”

To learn more about Social Communities, please contact us at info@seuratgroup.com

Predicting The Future In CPG

Predicting The Future In CPG

Predicting The Future In CPG

Predicting The Future In CPG

“An organization that doesn’t leverage its data in [a predictive] way is like a person with a photographic memory who never bothers to think.” – Eric Siegel, Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die

The Power of Predictive

Predictive analytics is as close as an organization can get to peering into a crystal ball. It is the answer to the billion dollar question: “what is going to happen?”

From projecting the effectiveness of door-to-door campaigning during the 2012 presidential election to forecasting the number of high-risk patients for healthcare providers in the US, predictive analytics provides a distinct competitive advantage to those willing to invest. The problem is that few in CPG have realized this potential.

Definition:
Predictive Analytics: The logical answer to the “what is likely to happen?” question. It is the practice of analyzing current and historical data to logically forecast future outcomes, trends, and behavior patterns.

Application: 
Predictive analytics enables companies to transform from reactive followers to proactive leaders.

Realizing the Predictive Potential

CPG retailers and manufacturers have mastered the art of descriptive historical analysis, which is valuable in its own right – for maximizing performance, reducing inefficiencies, and understanding how to better deliver against consumer and shopper needs.

Delivering against yesterday’s needs, however, fails to help these companies win in an ever-changing “world of tomorrow.” It skips the most important step in a powerful three-pronged approach1 to data analysis: prediction.

Predictive analytics has exploded across industries this decade. In fact, the use of predictive analytics more than tripled during the five years following the end of the recession, becoming a key strategy for unlocking growth.

Amazon is one company famous for its investment in predictive analytics, most notably to power its recommendation engine. Amazon’s predictive model is so effective that sales from recommendations account for more than 1/3 of total revenues.

The company is now turning its attention to a new predictive application: an anticipatory shipping model that cuts delivery times by shipping products to consumers, or in their direction, before they order them – all based on purchase predictions.

Spice manufacturer McCormick has also reaped the benefits of predictive analytics through its personalized recipe recommendation engine, FlavorPrint.

FlavorPrint initially gauges consumer taste preferences using a 20-question online quiz, and continually refines profiles by analyzing rated recipes and variables like weekday versus weekend patterns. It predicts which recipe recommendations consumers are likely to choose and when they are likely to choose them.

Thanks to predictive analytics, McCormick has captured a valuable competitive advantage in the digital engagement space. The company boasts 6 times more pages per visit to its website and an average website stay of 7 minutes5 – a number unheard of for most manufacturer websites.

It is programs like this that have made McCormick a proactive leader in CPG, contributing to the company nearly doubling its stock price over the past 5 years.6 There is a clear opportunity for other manufacturers to follow suit and invest in predictive analytics so that they too can transform from reactive followers to proactive leaders.

Applying Predictive Analytics in CPG

It’s clear that predictive analytics is a burgeoning game changer in CPG – the cornerstone capability for unlocking future growth.

Through years of helping clients leverage predictive analytics, we have identified 4 valuable applications across the industry:

Applications

2015 Examples

By leveraging predictive analytics to identify future consumer trends, a leading regional grocer optimized its portfolio of 20+ private brands down to 6 platforms well-aligned to current and future shopper need states.

End result: a strategic portfolio of brands that played well across all shopper segments.

The Clorox Company introduced a cold & flu Twitter conversation tracker that predicts flu incidence throughout the year based on volume of social engagement.

With this capability, Clorox can pinpoint peak flu season more effectively, and thus market cleaning products when and where consumers need them most.

A mid-sized manufacturer used predictive trigger analysis to identify factors that lead to the highest category spending.

This future-looking insight provided a more robust fact base beyond the usual category management metrics, and ultimately helped the company persuade retail partners to adopt its proposed guidelines – gaining share of shelf that exceeded share of sales.

A leading produce manufacturer built its long-term strategy based on forecasted purchase behavior. Using predictive analytics, it developed a future-looking decision hierarchy (PDH) that helped orient the business around a category-view of the behaviors predicted to unlock the greatest volume.

Conclusion

Tomorrow’s leaders will adopt predictive analytics as part of their foundational insight capabilities. It will take patience, careful planning, and a comprehensive strategic plan.

Despite these extra efforts, retailers and manufacturers that take strides to master the power of prediction will no longer act as passive followers, but rather proactive leaders capable of dictating the future. Companies that invest in predictive analytics will stay ahead of trends and drive growth, entering category whitespace before competitors get the chance to identify the same opportunities. They will be tomorrow’s leaders.

For more information on how predictive analytics can impact your business, contact the Seurat Group (info@seuratgroup.com).

MyClickstream: Connecting The Dots in Your Omnichannel World

MyClickstream: Connecting The Dots in Your Omnichannel World

MyClickstream: Connecting The Dots in Your Omnichannel World

MyClickstream: Connecting The Dots in Your Omnichannel World

Omnichannel Missing Link

Today, only about 1% of Consumer Packaged Goods sales are online. By 2018, that number is estimated to be 5%, with a full one-half of CPG growth estimated to be from online purchases.

Small brands are winning disproportionately online, gaining shoppers and engagement that can be parlayed into an in-store threat. For example, of the top 5 shampoos on Amazon.com, only 2 are available in brick & mortar retailers.

Winning online requires understanding the shopper’s full path-to-purchase in the increasingly omnichannel environment that shoppers are living in today.

Do you know how your shoppers are behaving online? Do you know whether those searches end up as purchases online or offline? What retailer they end up purchasing from and why? Is it better to invest in images, product detail content or in search? How does this differ between Amazon.com, Target.com, and Walgreens.com?

Manufacturers and retailers have expended significant resources toward understanding how shoppers are behaving and navigating in-store, but that same effort has lagged online.

This is because information on how to do this is limited, and manufacturers are hesitant to invest when approach and outcome are unclear.

Nevertheless, the time to understand omnichannel behavior and develop a winning strategy is now, before smaller, challenger brands take a permanent lead.

Limited Options Today

Few solutions exist today to fully understand and take targeted action against shopper behavior in order to grow brands online.

Current options rely on getting data from ecommerce platform owners, buying historical metrics from an online panel company, or conducting your own primary research by asking shoppers to recall purchase behavior and decisions.

Each one of these approaches comes with drawbacks around accessibility, flexibility, or accuracy. As a result, brands still lack the ability to develop a 360o view of their shoppers’ paths to purchase online and turn that into a truly differentiated omnichannel growth strategy.

The time is right to close this gap and begin to truly understand and anticipate shoppers’ changing needs. Doing so will provide the information needed to:

With the limited resource environment that most brands are living in, it’s critical to understand which elements online are driving shoppers to your brand.

Are they searching for your name or for your category? Are shoppers reading product content or reviews? What behaviors mark someone who buys your brand versus your competitors?

With the limited resource environment that most brands are living in, it’s critical to understand which elements online are driving shoppers to your brand.

Are they searching for your name or for your category? Are shoppers reading product content or reviews? What behaviors mark someone who buys your brand versus your competitors?

 

Find out what shoppers are searching for online and what they are browsing for that they can’t find or how they are being satisfied by your competitors.

 

Understand what shoppers react to positively and negatively online, and what marketing levers are more likely to lead to conversion or trade-up.

How to Connect the Dots in Your Omnichannel World

Closing these gaps requires the right custom data and approach to capture both what shoppers are doing in a specific category and why they are doing it.

Seurat’s myClickstream methodology gathers and integrates disaggregated data across the entire path to purchase. With this capability, we are able to answer a dizzying array of questions about shopper actions and motivations, ultimately allowing you to influence shoppers at the point of purchase by offering them the right solution in the right place at the right time.

Each of the three complementary data sets plays a unique role in understanding the shopper:

Shoppers download an app to their computer, tablet or phone, which captures every URL they click on.

These same shoppers in a panel share their purchase receipts in brick & mortar and/or online with us.

Shoppers take an attitudinal survey, allowing us to understand motivators: why they behave in the ways exhibited from passive tracking and/or purchasing data.

Through these three steps, we are able to understand
shopping missions and retailers chosen, navigation and trip missions, purchase decisions, and drivers/motivations to purchase across brick & mortar and ecommerce.

Being able to link this data at the household level enables deeper understanding of how online behaviors convert into purchases on and offline and can be used to generate actionable insights that will trigger desired shopper behaviors.  Additionally, this dataset is owned by you, enabling greater depth and flexibility of learnings.

This engine can be continuously mined to dig deeply to uncover new, compelling insights as new questions and needs arise. This ownership and deep level of detail enables you to engage in a highly customized way with your categories, your customers, and your shoppers.

The breadth of learnings achievable through myClickstream can be used to derive custom insights from the data to
arm the entire demand plan, ranging from customer and category planning to omnichannel leadership to capability development and marketing activation.

Contact us at info@seuratgroup.com or (203) 774-4900 to learn more about including MyClickstream to build your business online.

Delivering Idea Leadership

Delivering Idea Leadership

Delivering Idea Leadership

Delivering Idea Leadership

The world is becoming more fragmented, and so is data

The days of standardized (and commoditized) data in the CPG industry are over. Traditional sources of information come from sales and marketing channels that hold less and less dominance over today’s shoppers and consumers. From a marketing perspective, there is a massive shift of media dollars away from traditional media to digital media. From a sales perspective, growth is increasingly coming from “dark channels” not measured by syndicated data (e.g., eCommerce, alternative retail models like travel and bodegas, non-participating retailers like Trader Joe’s and Aldi).

Insight investment is being reduced, while teams being tasked with doing more

On top of zero-based budget constraints, insight teams are forced to use their limited time in collecting data from across today’s fragmented, omni-channel landscape. Many organizations are giving teams long learning agendas to identify and understand growth opportunities while providing less in the form of resources. A recent Seurat Group assessment of the insights practices of CPG companies found that many researchers are struggling in this environment.

If you want to catch big fish, you have to go into deep waters

Some things stay the same: companies struggle to translate information to insights and actions. Is fragmentation of data driving your insight capabilities into increasingly shallow waters? As resource constraints cause evergreen issues in research to accelerate, it’s even more critical to tighten the ideal leadership process to arrive at the clarity to act and invest in the future.

The Idea Leadership Pyramid
Insights teams play a pivotal role in high performing organizations by extracting relevant information from data, elevating that information to insights, identifying the implications for the business and eventually aligning on imperatives to action. The Idea Leadership Pyramid helps illustrate opportunities to increase organizational capabilities to identify and action deep insights.

The Seurat Group conducted a recent assessment on research and insights, and identified barriers and opportunities to deliver Idea Leadership across the pyramid.

Information
Ongoing Challenges

Consumer shifts and new ways of interacting with brands creates a wider variety of data to gather and analyze.

Solution

Continuously test new methods, such as passive tracking and social media analytics, to understand the consumer & shopper everywhere they are, online and offline, throughout the ever-changing consumer journey.

As ‘off the shelf’ studies like market structures are increasingly commoditized, challenging to uncover differential insight.

Customize research design for specific insight needs and use multiple lenses of information to create the foundation needed to identify deep insights.

Insights
Ongoing Challenges

Fragmentation of data assets, often in silos, inhibit the data connections necessary to fully understand the consumer/shopper.

Solution

Activate a knowledge management plan that integrates all available data and facilitates connectivity.

Resources are increasingly scarce while needs continue to increase.

Establish an interconnected data structure and actively mine data that already exists in the organization before fielding new work.

Research not keeping pace with a rapidly changing consumer and shopper landscape.

Ensure research is designed to be “forward looking” to increase relevancy beyond a single point in time and anticipate future challenges.

Implications
Ongoing Challenges

Research reports often focus on sharing facts and information.

Solution

Ensure the “what” is connected with the “how” and the “why” to better identify relevance in addressing business issues.

Application of information limited by exclusive understanding and/or ‘ownership’ by the insights function.

Insight teams must develop capabilities to teach the organization how to interpret insights effectively and elevate through every level of the pyramid through storytelling vs. reporting.

Imperatives
Ongoing Challenges

Gaps between internal stakeholder business needs and available insights.

Solution

Make idea leadership a cross-functional “team game” in both informal team structure and project process through all slices of the pyramid.

Conclusion

The ability of any Consumer Goods organization to understand the needs and deep motivations of consumers and shoppers and successfully commercialize those insights is THE differentiator between winners and losers in today’s marketplace. Elevating information to insights and action is filled with challenges at every level, and many organizations have barriers that must be removed to realize the full return on insight investment. As these issues accelerate with increasing fragmentation across marketing and retail channels, it is imperative to re-examine foundational research processes to foster game-changing idea leadership.

For more information on Idea Leadership, contact us at info@seuratgroup.com or visit our website: www.seuratgroup.com.