- How to Succeed in Consumer Packaged Goods with Data and Analytics
- Analytics for CPG Roles Within Marketing and Sales
- Common CPG Problems Solved by Augmented Analytics
- How AI and Machine Learning Can Transform Your CPG Analytics Approach
- What Self-Service Analytics Means for a CPG
- Helpful Webinars
- Picking the Right Analytics Solution for Your CPG Company
- Request a demo
How to Succeed in Consumer Packaged Goods
with Data and Analytics
1. Get a complete, up-to-date rundown of your current performance.
With an agile and smart analytics solution plugged into your data, you can perform the kind of in-the-moment reporting and analysis that will help you move past the competition.
From big-picture analysis like assessing marketing effectiveness and evaluating key performance indicators (KPIs) to more granular work like monitoring product availability and preventing out-of-stocks, the ability to conduct up-to-date research and reporting can prove pivotal.
Look for solutions that let you build dashboards as you go, rather than working from static reporting that was built months prior to support previous targets and business needs.
Real-time analysis gives your team the flexibility to make changes that have an immediate impact, rather than waiting to execute a retroactive fix.
2. Identify your biggest growth opportunities, and forecast future performance.
When it comes to the data itself, leading companies secure comprehensive data from retailers and third parties, including full-basket and shopper-panel data as well as loyalty-card and coupon-redemption data.
To edge out your competitors, work with a CPG analytics solution that can help you sift through the copious amounts of data and quickly make sense of it.
You need to be able to look at your own data as well as syndicated data, so identify an analytics solution that gives you instant access to all that you need. You don’t want your team to spend its time searching for answers. Instead, they should be thinking critically about how to make meaningful decisions based on those answers.
With the right solution, you should be able to investigate your sales pipeline to track your leads, selling stages, average time to close, and more. On the marketing side, you need the ability to perform churn analytics to find changes in purchase tendencies and save at-risk customers. You will also want to perform attribution studies to see which channels are profitable and which are not.
And finally, look for a solution that helps you review the customer journey to gauge user tendencies across your omni-channel presence.
Analytics for CPG Roles Within Marketing and Sales
Common CPG Problems Solved by Augmented Analytics
Due to growth in omni-channel distribution and evolving customer behavior, decision making for CPG leaders like CMOs is more difficult than ever.
In every facet of the field, the expectation is clear. To succeed you must make aggressive decisions backed by ample data.
From adjusting SKU portfolios to asking retailers for assortment changes to trade-promotion management and much more, each move your CPG makes is better served by an insights-driven analytics platform. So, consider making the switch to an augmented solution that offers data visualizations alongside actual insights that help you gain a deeper understanding of the trends and results.
Then, leverage the power of AI and machine learning alongside the collective mind of your team for maximum results.
As is explained in “Competing in the Age of Artificial Intelligence” from Boston Consulting Group’s Henderson Institute, “It is critical for companies to figure out how humans and computers can play off each other’s strengths as intertwined actors to create competitive advantage.”
The CPG space is evolving, and it can be hard to keep up and ensure you do not lose market share or miss opportunities as things change.
As more and more data becomes available and consumer behavior makes the market less predictable, forecasting brand and product performance becomes increasingly challenging.
Approaching your data with an augmented analytics solution can be just what you need to get a grasp on the current state of the market and make decisions accordingly.
Not only will the right analytics solution provide question-by-question insights, but it should empower your team to synchronize its decision making.
More and more CPGs are seeing the benefits of a combined effort across sales and marketing, and working with a cross-functional analytics solution democratizes the data analysis process while making insights generation more efficient, consistent, and clear.
Clarity in the decision-making process should help you with: ensuring you are producing the correct size and quantity of all your products, sending the right mix of products to each location, and in general, aligning efforts across marketing and sales.
Without an augmented analytics solution that presents your data and insights to go along with it, your team has to rely on someone else to do the reporting.
This often translates to a business user having a question, asking for a report on said question from your analytics division, waiting a few weeks for a response, and receiving a thorough answer that does not account for follow up.
Using a solution that can handle natural language requests and turn out insights alongside basic answers means that you cut out the weeks-long process and allow for easy follow up from team members.
When your approach to data is siloed, you run into issues. By democratizing access, meaning all necessary members of the team can generate and review reports, you open the door to more curious and advanced thinking.
Consider how this plays out with the following example.
Your CPG uses a traditional business intelligence platform. A category manager puts in a request to the analytics team and asks for a very narrow report. A few weeks later, when the report comes back, it is not quite what the category manager wanted. From there, she can ask for another report, which would put that idea weeks behind initial conception. Or, she could move forward without getting exactly what was needed.
The misstep there is not with the analyst or the category manager, it is an inefficiency in the process. The process is not agile; it cannot quickly account for an evolving need or a secondary and related request.
Whereas with an augmented solution, drilling down is as simple as asking a second question in a search bar. No time is wasted and no question goes unanswered.
The CPG industry has been forced to evolve rapidly in response to an increasingly omnichannel market with shifting demographics and changing shopper preferences.
This evolution has been made easier by the advent of AI-based analytics platforms that automate laborious data analysis and enable users to ask questions of their data. As more companies trend toward expanding their IT budgets and investing in this automation, the CPG industry can become more and more agile.
With the right technology, getting quick answers to complex questions can become standard practice, and businesses who don’t adapt may struggle against their competition and yield to growth opportunities that require fast, proactive strategizing.
However, the true power of this new wave of business intelligence lies with the non-technical users who encounter the CPG marketplace in their day-to-day work — business people who drive strategy and are well-positioned to immediately act on the information they learn from asking questions.
That’s why augmented analytics are so key; incorporating natural language into AI enables non-technical people to use the software, which means business people can update their strategy and respond to the market as it changes, rather than after-the-fact.
CPG Case Study
How One CPG Company is Winning with an AI-Powered Analytics Platform
A leading consumer packaged goods company was looking for help in two areas. They needed to identify more growth opportunities, and they wanted to do so quicker than they had previously. So, they turned to AnswerRocket.
Discover how our analytics platform is helping their consumer insights team efficiently answer key questions related to brand health, competitor performance, and gaining market share.
How AI and Machine Learning Can Transform Your CPG Analytics Approach
Easy to Use
When researching AI-powered analytics platforms for your CPG, look for a solution with a natural language search feature and an incredibly intuitive user interface.
In practice, that means your business users can type their questions directly in a search bar, almost immediately receive an answer (think Google), and drill down from there. No special training is needed, and non-technical users have full control over the reports they run.
Thanks to the inclusion of natural language search and valuable data visualizations, non-technical users no longer have to wait days or weeks to get their questions answered.
Rather than requesting a report from a very busy analytics team, your typical user (such as a category manager) can type their question in and receive a detailed report in seconds. This frees up your business users and your analytics team, allowing your CPG company to forge ahead of the competition.
Beyond answering the questions of non-technical users quickly, the most advanced platforms also offer insights. The depth of insights will vary from platform to platform, but you want to identify a solution that can synthesize your data and present you with key takeaways and actionable findings.
With the help of AI and machine learning, the leading analytics platforms can handle multiple enterprise-level data sources and sift through thousands of data points to isolate the biggest opportunities for your consumer goods company.
The current and future value of insights should not be undersold. Nilam Oswal put it well in her article for Dataconomy. She explains:
AI offers better insights than ever before. AI is, essentially, automation of the maximum sequence of decisions originating from prescriptive analytics. Its intelligence comes from its ability to give real-time feedback data to enhance prescriptive models. This ensures that the next prescribed decision will automatically be better than the previous. This exceptional ability to adapt and learn enables AI to execute actions following automated decisions. As organizations continue generating more data, the analytical might of AI will help power the next phase of decision-making and profitability.
In other words, actionable insights are the future of modern business intelligence.
What Self-Service Analytics Means for a CPG
As the name implies, with a self-service analytics platform, the power is in the hands of the user.
In practice, this means that a non-technical person can take their plain English question, type it into the software, and receive a comprehensive report in seconds.
There’s no middleman. There’s no request queue. There’s no long wait. Answers come directly to the person asking the question.
Analysts are not being replaced by self-service analytics solutions. Rather, analysts are no longer tied up running basic queries for their less-technical colleagues.
Instead, analysts can focus on higher-level, deeper digging. In the end, your CPG gets its ongoing business intelligence questions answered while your analysts can leverage their new time to push your performance even further.
Self-service analytics platforms offer consumer packaged goods companies something that is immensely valuable: the democratization of data.
With a traditional BI solution, your typical executive is a few steps removed from the company’s data.
Often, that means that valuable questions go unanswered because people do not want to go through the hassle of getting a report. It also means, that when questions are asked and answered, there is not much of an opportunity to drill further into the data without diving back into the cumbersome reporting process.
With a self-service platform, anyone on your team can take their question directly to the data. That openness of data will be crucial to your CPG’s continued success in this increasingly competitive market.
For an example, consider what happened when SnapAV installed AnswerRocket’s analytics platform. As Adam Levy, SnapAV President, explains, “AnswerRocket made it easier for our employees, including myself, to be curious about the facts in our business.”
Thanks to the self-service nature of our analytics platform and the curiosity directive led by Levy, SnapAV was able to unearth a $1M opportunity after a few minutes and only asking a few questions.
Using AnswerRocket, SnapAV’s team is no longer chasing down answers. Questions are now answered almost as quickly as they can be asked, fostering the curiosity to dive deeper.
As we explain in our blog post on FMCG analytics (fast moving consumer goods, a large subset of the CPG industry):
With omnichannel sales and marketing, people have more choices than ever before about where they’ll spend their money and how they’ll engage with brands. Plus, connected consumers have access to tons of product information at their fingertips, which means they’re more discerning about their choices than they’ve been previously. Likewise, companies have more touchpoints with customers, though catching consumers’ attention can be a challenge when they have so many options available and a plethora of ways to spend their time. Such a dynamic landscape requires a dynamic analytics solution than can understand and interpret data quickly.
Getting expedited results on how your marketing campaign performed is an example of how immediate insights and democratized data play out in real life. With self-service analytics, the only lag time before reporting is the actual data collection.
By putting the power in the hands of your marketing team, as soon as the data is collected, your team can run all sorts of marketing analytics reports, including campaign ROI calculation.
There are two levels to this self-service benefit.
First, your business users, like brand managers and consumer insights experts, can more immediately access and drill into reports regarding brand health. They simply type their questions into the platform’s search feature and build out their own dashboard. With every specific question (think: “what were sales and market share of X by month last year”), your non-technical users are aiming to get a deeper knowledge of broader brand health questions, such as:
- What is the overall performance of Brand X?
- How is Brand X performing in the Channel Z?
- For Brand X, what is the current status across the 4Ps?
- What are the top 10 growth opportunities for Brand X?
- What are our growth and retraction drivers?
- What should we do to recover/gain market share?
If your company has a solid answer to each of those questions, you’re in great shape to strategize for much stronger future performance.
For more advanced reporting, the second level of this self-service benefit comes into play. Freed from helping non-technical users with their more rudimentary queries, your analytics team can take the lead with deeper analysis and modeling. Given the fact that they will no longer be tied up by basic requests, they can dedicate valuable time to furthering your company’s understanding of its brand health.
Thanks to the immediacy of the self-service process, it is easy for a user to come up with a theory about consumer behavior and then test said theory through reporting and analysis.
Rather than a drawn-out process, everyone from product and brand managers to consumer insights specialists can dig into the available data and draw valuable conclusions about customer need and behavior.
How CPG Companies are Driving Meaningful Business Results with AI
In this Food Dive study, 72% of business leaders were found to believe that AI delivers a business advantage. Learn more about how AI can synthesize omnichannel data and encourage data-driven decisions.
Picking the Right Analytics Solution for Your CPG Company
The field of analytics solutions is quickly evolving. If you do not transition to a forward-thinking platform, your consumer goods company is at risk of being edged out by your competitors who do take advantage of the new software options.
However, the decision to invest in a new analytics platform should not be taken lightly. As an enterprise-level CPG, you cannot afford to make the wrong choice.
So, where does that leave your business?
It means you need to review the field and choose a platform that complements your goals and provides insights beyond what your team is currently capable of discovering.
There are endless ways in which you can analyze CPG analytics software, but to get started, we recommend the following list of seven selection criteria:
- Is there a truly user-friendly interface for business users (think: CMOs, brand managers, category managers, etc.)?
- Are the data visualizations intuitive and readily digestible?
- Is there a feature that provides deeper insight or next-level thinking?
- Is the solution open and flexible to any data source?
- Can you access the platform on mobile devices?
- Will the vendor be able to get up and running smoothly and efficiently?
- Will your data be safe?
If you can answer yes to all of those questions, the platform is in good shape and worth further consideration.