Data Analytics: Six compelling reasons to dive deep for big returns

Transcription

1 Data Analytics: Six compelling reasons to dive deep for big returns Jean Nickerson, CSP Senior Consultant Marketing Data Solutions February 2015 This article explores several opportunities for the B2B marketer to use data analytics to reduce marketing costs and increase revenue. Predictive analytics is the art of identifying and harnessing patterns in data to effectively prospect new customers and leverage the most out of existing customers. Companies such as Netflix, Amazon and Trip Advisor are masters at using predictive analytics. These companies use up-to-the minute data to target their marketing efforts with precision; delivering relevant and timely content to their customers. Netflix knows that you like Hollywood action adventure films, while your teens prefer the comedies. If you check out Amazon for a new coffee maker, your inbox will percolate with specials on the brands you spent the most time looking at on their website. Start researching a destination on Trip Advisor and you ll soon get updates with hotel price point drops and deals on airfare.

2 From a marketing point of view, it may look like magic but it s not. What customers see is the result of in-depth analytics and math. Successful consumer marketing companies, like those mentioned above, have harnessed the power of taking data from multiple sources coupled with statistical methods to analyze and predict buyer behaviour. Compared to consumer marketing, however, the use of data analytics in B2B (business to business) marketing is in its relative infancy. We are only seeing the tip of the iceberg, to use a valid cliché. That s good news for those who are trying to gain a competitive advantage. Predictive analytics in the B2B space is less developed because it is exponentially more complex. The data comes from more sources and there are personal salesperson-to-customer relationships involved. An article which appeared in the August 9, 2012 edition of Harvard Business Review 1 purports that when you think about big data for your sales organization it needs to be more about big insights and must be specific and relevant to the sales force using it. So what will predictive analytics do for the B2B marketer and how can you begin to build these vital assets? This article explores six key ways data analytics can help you increase productivity, prospect and market more effectively, and potentially make a positive impact on your bottom line either through reduced costs or increased revenues. Predictive analytics in the B2B space is exponentially more complex because the data comes from more sources and there are personal salesperson-to-customer relationships involved. 1. Increase the productivity of your sales force Using analytics to qualify sales leads is one key way you can harness data to drive revenue. This sounds obvious, but here are two interesting statistics that point to the opportunity. 61% of B2B marketers send all leads directly to Sales; however, only 27% of those leads will be qualified. Just 56% of B2B organizations verify valid business leads before they are passed to Sales. (MarketingSherpa) 2 When it comes to lead generation it should be about quality, not quantity. Lead scoring a methodology that is used to qualify leads is often based only on a company s internal or CRM (customer relationship management) data. To further qualify leads you can add firmographics data to the mix. Firmographics typically include details about a business s industry, location, employee size and annual revenue, etc. that are available through a variety of public sources. 3 To enrich the analysis you can add risk and credit variables to incorporate prospects financial health and ability to pay. The combination of firmographic information with risk data allows marketers to optimize 1 For Sales Forces, Big Data May Be Overhyped, Harvard Business Review: Andris A. Zoltners, PK Sinha, and Sally E. Lorimer August 9, Nurturing-Stats-You-Can-t-Ignore.aspx 3 The table in Appendix A shows a variety of firmographic information you might use to develop an understanding of your commercial customers.

3 response and ensure that the potential clients they attract are ones that fit their risk profile. You may not want to do business with a company that has shown a persistent pattern of delinquent payments or more fundamentally, bad credit behaviour. FIRMOGRAPHIC FILES CREDIT & RISK INFORMATION CRM DATA Leads qualified by a business s ability to pay can save your sales people valuable time and resources 2. Break down silos between marketing, sales and risk departments The other advantage of developing an enriched lead scoring capability using credit and financial data is that it can lead to better relationships between departments. In many B2B organizations the last stage of onboarding a new client takes place in the risk department. What happens when a potential new customer doesn t qualify as a good credit risk and can t be onboarded? A sales person may have spent months wooing a client only to find out that their company doesn t want them on the books. When leads are qualified using risk data, your marketing and sales teams can learn early on in the cycle which prospects have a higher value and which ones don t. The potential confrontations that plague organizations when the marketing and risk departments aren t working together disappear. Incorporating risk data into this process can better qualify your sales leads; and can also serve to foster greater relationships between departments that often find they are working at cross purposes. 3. Nurture your prospects and existing customers more effectively As you begin to understand and segment your prospects and clients through data analytics you can target your communication with them based on their specific needs. Lead nurturing activities that are specific with offers deemed valuable in the eyes of the recipient, could help you convert more leads into satisfied clients. According to Annuitas Group, a firm which specializes in demand generation strategy and technologies, businesses that use marketing automation to nurture prospects experience a 451% increase in qualified leads. 4 Lead nurturing campaigns can consist of updates and links to educational resources such as articles like this one. Why lead nurturing is important is that it takes an average of 10 marketing-driven touches to progress a lead from the top of the funnel to the top line (i.e. revenue). (Aberdeen Group) Create competitive edge Early adopters of a predictive analytics strategy could potentially reap huge sales increases while your competitors watch and wonder how you re doing it. They may eventually figure it out but gaining this early lead and employing new best practices could help you develop a sustainable competitive advantage. Best practices include knowing the expected impact of your marketing investment; quantifying forecasts and results in terms of leads, pipeline and revenue as well as implementing marketing metrics (including those that measure quality) to measure performance. According to Thomas H. Davenport in his article for Harvard Business Review 6 marketing has always been tough to quantify but with widespread use of modelling and optimization, an enterprise wide approach and senior executive advocates, a pro-metrics organization can be built and sustained. Davenport states, Virtually all the organization we identified (in this study) as aggressive analytics competitors are clear leaders in their fields, and they attribute much of their success to the masterful exploitation of data Thomas H. Davenport, Competing on Analytics Harvard Business Review January 2006

4 5. Increase cross-sell and up-sell opportunities When you receive a new credit offer in the mail shortly after moving into a new home, it s not a coincidence. Using your income, geography, postal code, marital status and home value, the savvy marketer behind this campaign targeted you based on the higher likelihood of your needing more credit.to buy new furniture or appliances perhaps? B2B marketers can also use financially-based data to zero in on events that result in benefits to your company. For the automotive supplier it might be the expiration of a fleet s auto lease agreement. For a lab equipment manufacturer it might be newly funded labs. For a company that sells office equipment it might be a new real estate lease - indicating the prospect is moving to a new office. For an industrial parts distributor, it could be understanding who is registering construction liens. Data Analytics: Six compelling reasons to dive deep for big returns 6. Segment your customers like they do in the consumer world and spend your marketing dollars wisely Are you leveraging your prospect and customer data to score attributes, build discrete segments and allocate resources to maximize the conversion and revenue as they do in consumer marketing companies? A leading Canadian company in the Utilities sector recently hired Equifax, a leading source of consumer and commercial data, advanced analytics and technology, to help them segment their 68,000 customers based on profitability scores. They determined these scores through a deep analysis of their customers across Canada using specific data attributes to determine profitability. At the outset of the project they knew who their top customers were by revenue. The company s aha moment was discovering a higher-than-expected profitability amongst 30,000 second- and third-tier customers. They re now using this knowledge to specifically address the needs of these groups with an end goal of migrating these businesses into even better customers. This exercise also allowed them to better allocate their marketing budgets to campaigns that yielded higher ROI. By knowing the profitability of each customer group, a simple tactic such as being more specific about who receives your latest promotional offerings (and who doesn t) can yield better results. In addition, understanding what makes a customer profitable can help you develop a model that will enable you to invest more in acquiring and nurturing companies which more closely match your ideal client profile. By adding risk and credit data to the mix you can further qualify leads based on your prospects financial health and ability to pay.

5 Appendix A: Firmographics Variable Data Variable Data Age Size Financial Decisions Ownership Market Position Years in Business Stage Number of Employees Number of Locations Number of Plants Sales Profits Credit Rating Headquarter/Subsidiary Branch Public Company Private Company Government Non-Profit Market Size Number of Potential Customers Market Structure Market Share Industry Position Trends Customers Property Residency Manufacturing Technology Product Life Cycle Industry Life Cycle Growth Decline Stability B2B B2C B2E B2G Lease Plant & Equipment Own Plant & Equipment Length of Residency Discrete Manufacturing Process Manufacturing High Tech Low Tech Early adopters of a predictive analytics strategy could potentially reap huge sales increases while their competitors watch, wonder and worry about their own capabilities.

6 Preparing for the Dive So how do you prepare to delve into the data? Many B2B companies don t have the sophistication or the resources to navigate through big data. Leading edge B2B marketers are beginning to put the foundations in place. There is so much data out there, says Regina Malina, Senior Director of Decision Solution Analytics at Equifax. Many of our clients say, Please just give me a compass so I can understand what is relevant to MY business and what will help me achieve MY objectives. Data driven marketing requires a set of skills that are hard to find in many B2B organizations. Equifax addresses these skill gaps with analytics capabilities that can be used as another tool to assist businesses in their growth and development. Data Analytics: Six compelling reasons to dive deep for big returns A mid-sized Credit Union with a limited budget and no analytical staff in-house asked Equifax to help them find new business opportunities within their existing customer base. The analysis compared and contrasted customer segments based on a variety of credit attributes and revealed that a subset of their small business clients had substantially more new credit inquiries than other segments. For this group Equifax was able to pinpoint those customers who would be more likely to take up the offer of a new business credit card. The ROI of these data driven marketing tactics can be easily calculated. In this example, there were 10,000 small business customers in the likely to buy segment. A 2% conversion rate (200 customers) and an average $20,000 worth of annual purchases using that business credit card could easily result in $4 million in new business. Predictive analytics and the right data-capture mechanism can assist you in identifying a customer and/or prospect s propensity to engage with you, their propensity to buy, their lifetime value to your organization and their attrition risk. You can use data analytics to determine best product offerings, preferred communication channels, and the right marketing communication messages. The bottom line? Using predictive data analytics in your B2B marketing initiatives can help you make significant inroads. These initiatives could result in increased productivity, profitability and business growth. Start with dipping a toe and you ll soon be diving in with both feet. You can contact us to find out how Equifax Commercial Marketing Solutions can help you develop data-driven marketing activities. We welcome the opportunity to discuss your marketing goals and objectives. Contact Us Today Call to speak to an Equifax Advisor or visit us at Equifax and EFX are registered trademarks of Equifax Canada Co Equifax Canada Co. All rights reserved