Let’s move ahead from the ‘what worked and what didn’t’ discussions of 2017 to reflect on the emerging trends in 2018. The B2B segment is becoming highly competitive and customer acquisition costs are rising. Though there is no dearth of customer data, tapping, filtering and analyzing all of it is tedious and costly. Companies are constantly looking for effective ways to utilize this data for a better ROI.
Nevertheless, the first and foremost requirement for an enhanced ROI through analytics is the quantification of the company targets to reach the expected ROI figures.
1. Quantify Your Marketing Plans: What, when and how to measure should be clear. Though it might appear difficult to set standards to measure ROI of each channel, web analytics tools can prove quite useful in measuring statistics from social media and other online marketing campaigns. Gather all relevant data and analyze it before, during and after a marketing initiative to measure the impact of the initiative and the expected outcome. However, be sure to focus on the right kind of data.
2. Focus on the Right Data: Some typical metrics may be suitable for public display but may not be major contributors to revenue. Twitter followers, Facebook fans or likes may make your marketing campaigns more appealing, but what really matters is metrics like lifetime value, cost per acquisition, product ratings and number of active users, queries generated as a result of your campaign, and so on. Hence, the focus should primarily be on the engagement metrics that equate to ROI, rather than the ‘visibly good’ metrics. At the same time, the customer data gathered should be accurate and detailed.
3. Ensure Data Accuracy: Data is the key to an effective output. Poor data can lead to lost opportunities, time and effort, and eventually – lost revenue. Hence, make sure that the data you are about to analyze is accurate and thorough. Besides data accuracy, you should also be aware of the customer type and customer behavior you intend to replicate based on your business objectives. For this, ensure that the data that reaches your CRM is clean. Pick and choose relevant datasets or contact lists for analysis based on what you want to predict – your quantified objectives.
4. Use Predictive Modeling in Data Analysis: Traditional teams relied on frantic cold calls without a scientific way to predict if a particular contact in their list is a potential lead or not; predictive modeling, instead, uses data mining and algorithms to spot potential customers, track leads systematically and land up with the most accurate prediction based on historical success. This surely shortens the list of potential customers enabling focused efforts, yet the success of this endeavor in terms of enhanced ROI depends primarily on the opportunity to timely tap into the behavioral indicators for active demand instead of merely being aware of these indicators. This points us towards intent signal monitoring insight for more productive conversations and effective sales.
5. Use Intent Data: Intent data is data collected about a web user indicating some intent or future action based on person’s online activities. Picking up these digital clues about interests and intentions of people can help keep a pulse on the target audience at every step of their buying journey. This data helps locate potential buyers you can approach strategically to convert them into real buyers. While first-party intent data may not be sufficient in helping you elicit the results you need from your marketing campaigns, hence, this data should be complemented with additional intent data from third-party data providers. Vendors like Bombora and Big Willow can help you identify target accounts in the active demand mode. You can then create focused nurture programs, deliver content that the audience wants, and convert them faster and more efficiently and effectively leading to a higher ROI.
Though following this route definitely helps but don’t shy away from experimentation. Involve your marketing and sales teams and try new tactics. Recreate your marketing mix, use available metrics to understand if the current product can be improved, and make informed decisions.
Do not focus on merely collecting more and more data rather set a data limit and ensure that data analysis is conducted appropriately and that all analytics reports include action items. And, follow-up on the decisions made. Wish you luck in your marketing endeavors!!