The new year represents a fresh beginning and a chance to make positive changes. Whether those resolutions are about being more fiscally responsible and saving money, or aiming for a healthier lifestyle by not eating that second slice of cheesecake (guilty as charged), resolutions intend to help us improve and be the best we can be.
Companies are no different. They too share similar goals and set resolutions in an effort to achieve success. Of course, setting a resolution is the easy part; keeping it is much harder, and is something companies have an advantage with thanks to analytics.
Here are a few of the most popular New Year’s resolutions that companies across the globe are making in 2017, and how analytics can help keep organizations from breaking them.
1. Grow the Business
Not surprisingly, every company looks to increase profits and grow the business year-over-year. After all, growth is the lifeblood of the organization. And while everyone is pointing to data as a conduit for growth, the real opportunity comes from the insights that are developed to create foresight into business opportunities. That begins with analytics.
Growing your customer base is an obvious strategy to drive growth, but one that is more challenging than ever before. With so much competition and information out there, it’s hard to reach and engage your best prospects. Sure, we have tons of data at our disposal, but is it accurate? And what does it tell us about capitalizing on new opportunities? By leveraging advanced analytics, you can produce models to help you narrow your target universe and isolate high-value prospects by estimated financial outlook, demand, and spend potential for your products and services, as well as incorporate firmographic and behavioral data to increase response rates and accelerate time to close. Ultimately, it’s analytics that helps you understand your target audience and win new customers. Data alone won’t do that.
While acquiring new customers certainly helps drive growth, let’s not lose sight of current customers and the role they can play in growing the business. Expanding the focus beyond just acquisition will ensure you are not leaving revenue on the table by not optimizing further down the funnel. Analytics can help identify key up-sell and cross-sell opportunities to increase your share of wallet with existing customers.
Many analytics models can be designed to provide a clear understanding of your customers’ exact needs so that you can prioritize and streamline the products and services you offer them at the right time. These insights can also pinpoint customers with the highest level of buying authority to help you focus your efforts and dollars on the right audience and grow revenue.
Through a combination of prescriptive and predictive analytics, you can also gain a deeper understanding of the customers most likely to fall by the wayside so you can proactively impact retention rates. Analytics models can help align customer service resources with the right opportunities and prioritize channel and territory assignments based on future outlooks and external factors. All of these models will help keep your growth trajectory on track in 2017.
Dun & Bradstreet itself has been aggressive in using analytics to improve sales and marketing. “While working with our customers to boost their targeting strategies, we have seen more than a 20% improvement in their conversion rates by leveraging models that add behavioral data, activity signals, time-series triggers, and other layers of predictive insight on top of basic firmographic data and past internal purchase history,” says D&B’s Chief Analytics Officer Nipa Basu. “Accelerating the use of analytics using expanded data and advanced techniques is turning that improvement into significant revenue growth for our customers and remains a key strategic priority for us as we move into 2017.”
2. Build Stronger Business Relationships
Relationships are the longest-standing, most proprietary differentiator for any company. At the end of the day, the most successful companies are those that value relationships above all else. It’s no wonder companies are prioritizing strengthening their relationships with customers, vendors and suppliers in 2017. But in today’s complex business environment, it’s often a challenge to grow relationships with companies where your knowledge of their business is not fully understood, or limited at best. That’s why many organizations are starting to recognize the importance of data that provides meaning or context for a deeper understanding about the companies they do business with. But the real value comes out of the insights you’re able to glean from that data.
By closely analyzing this “relationship data,” you’ll begin to infer the nature of your global relationships moving forward. What potential behaviors and actions might an entity engage in, and what impact will that have on your business? Once you’ve identified the most valuable relationships within your organization, you can derive analytics that help predict better outcomes that lead to improved results. These decisions ultimately affect the success of your business.
For instance, recognizing the current challenges, opportunities or other situations that you may or may not have yet to consider about your partners can change how you do business with them moving forward. Through analytics, you can discover connections and associations that can help inform more prudent decisions that can impact your approach toward pricing, terms, risk and more. The data (trade data, shipping data, public legal documents, etc.) enables you to interpret signals that create meaningful insights on inter-company business dealings that can help drive your business strategies and strengthen your relationships with the most valuable partners. From predictive scores and indexes to payment data growth monitoring, you can build custom analytics to help pinpoint weakness and opportunities. Ultimately, these data points enable you to move beyond simple modeling based on internal historical data, and produce sophisticated business models grounded in multifaceted business connections.
“It is no longer good enough to have predictive insight that is an inch deep and a mile wide,” says Basu. “To create actionable analytics with higher degrees of precision and discriminatory powers, it’s imperative to look at data points such as credit inquiries, trade relationships, and shipping and delivery data to differentiate between businesses, which on the surface, look exactly alike. My team of data scientists are finding innovate ways to use these new data points to overcome gaps in traditional data and help our customers achieve the required levels of global consistency, coverage, and predictive performance.”
3. Be More Socially Responsible
Over the last decade or so, there’s been a huge increase in the number of organizations prioritizing time and resources to be better “corporate citizens.” Commonly referred as corporate social responsibility (CSR), this is an initiative that sees organizations balancing their aggressive revenue goals with a commitment to giving back to the community and pledging to be ethically responsible. This can mean anything from helping conserve water and energy to reducing waste and pollution, and even helping combat social injustices. Analytics can be used to address where many of these issues lie, helping companies understand exactly how they can get involved and make a difference.
One area that has recently emerged as a focal point of corporate social responsibility is the supply chain. Unfortunately, some 34 million men, women and children worldwide are living in modern slavery through the practice of forced labor. Companies may unwittingly be doing business with enterprises that employ this despicable practice. It’s why understating your business relationships is important. Analytics can be used to not only identify where this may occur, but help combat the practice.
Dun & Bradstreet is utilizing analytics to do just that with its Human Trafficking Risk Index. The analytic model marries U.S. Department of State data and International Labor Affairs Bureau data with proprietary data from Dun & Bradstreet’s global corporate database to spotlight suppliers in geographies and industries most likely to be exposed to human trafficking. This enables companies to effectively make responsible sourcing decisions, develop plans to avoid brand damage and to comply with regulatory demands.
For example, as forced labor is more likely to occur in certain geographic regions and product sets, data creates an analytic index that evaluates the potential for one of your suppliers to be involved in human trafficking based on the location of the supplier and the product or commodity type they provide.
“Eradicating the practice from your supply chain is critical,” says Basu. “It’s not good business, it’s the right thing to do. By leveraging this data, models can be produced that can help you understand the risks within your supply chain and proactively assess suppliers for the risk that they have been involved in modern slavery.”
No matter how much you and your organization are determined to see these goals through, be sure to apply analytics to guide you to making your 2017 resolutions a reality.