Pro Tips for Generating Leads from Data Analysis
The balance sheet is where it all matters in the end. But turning insights from data analytics into attractive accounting numbers is a journey often filled with twists and uncertainties for the small business owner.
That is where this article comes in.
For the umpteenth time, data collection and data analytics are critical to the success of your business. However, lead generation and conversions from your data analysis are far more important than the data analytics itself.
For instance, Server Density, a server monitoring company, discovered that bigger discounts for clients with smaller budgets didn’t increase conversion rates or revenue. So, Server Density realigned its pricing with customer success¹, i.e., bigger paying customers got bigger discounts.
As a result, the company recorded fewer sales turnovers but a whopping 100% increase in its revenue. Why? Attempting to capture a wide net of less-paying customers didn’t increase revenue or conversion rates. The big-spending clients were the deal for their business.
This short post will draw out clear strategies for you to understand market trends that can generate good leads and conversions for your business. Let’s get to it.
1. Identify the Pressure and Pain Points to Influence Customer Behavior
Like it or not, the art of marketing is to apply pressure on customers or prospects. Think about time-bound discounts, flash sales, bonuses, coupons, etc. The pressure often varies depending on different factors, but it is nonetheless.
For Amazon, one of its biggest revenue schemes is to analyze big data to predict, target, and influence customer behaviour.
During the 2008 – 2012 American recession, Amazon grew its sales in North America by 30% to 40% because it invested 5.6% of its sales in IT (the highest among its competitors)2. That investment resulted in a super-intelligent algorithmic recommendation system that feeds off big data.
But that was not the defining moment or move. Two things set Amazon apart from its competitors. It used big data to:
- Predict near-perfect recommendations and upsell other products to customers (pressure); and
- Act on customer complaints in a more personalized fashion (pain points).
It is not unlikely that when you call Amazon customer service, the representative already has most of your details and can address your complaints with ease while providing the best alternatives.
The lesson here is to understand your audience and influence their purchasing behaviour.
Do they love discounts? Do they like to read more text about the product or less text, more pictures? Do you generate more traffic from your mobile applications? Then, reduce the third-party in-app ads while you pile more energy on simplifying the user interface and enhancing customer engagement.
Once questions like those listed above are answered, you can create a well-defined strategy to target prospects and generate so many leads that can change the numbers on your balance sheet.
2. Data-Driven Decisions Are the Best, but “When in Doubt, Simplify”
It would be pretty rare to meet a prospect who likes complicated pricing or a complicated website.
Understandably, small business owners face the temptation to overload their website with information or their landing pages with all their products. But it is a bad move.
First, your data analysis and expenditure sheet do not reveal a clear pricing strategy; it is best to be simple and straightforward. You risk losing prospects to competitors with less complicated plans if your pricing is too complex.
Apple’s Smart Pricing Plan
Apple products are not likely to come up with discounts, yet they are in high demand. The company focuses on creating great products with an incredible user experience. The Minimum Advertised Price strategy contrastingly keeps the products’ popularity in the market3.
Second, a simplified user experience on your website is better than a website that gives the prospect a maze-like experience. LaQuinta, a limited hotel service company in the U.S., revised its website designs and functions to show more pictures to visitors and to remember customers’ preferences among a host of other changes. It was after visitors filled a survey to the website. The result was an 83% year-over-year revenue growth4.
The lesson here is that your pricing strategy and branding are precious to lead generation strategies. The best decisions are data-driven decisions, but when in doubt - simplify.
3. Perfect Sales Funnel and Customer Retention Strategy
Earlier in this post, we illustrated how Amazon increased its sales by investing in a super recommendation algorithm and customer care service.
A research report by Bain & Company showed that profits could increase up to 25% when customer retention rates go up by 5%. The reason is that recommendations from loyal customers can boost sales better than ads in many instances5. Recommendations can come from social media feedback (especially in the age of e-commerce) or word-of-mouth.
Chick-fil-A restaurants are famous for their customer retention and loyalty schemes6. They have generated enough revenue to pay store operators a double or triple of the average rates in the industry.
4. Invest More in Targeted Advertising
In 2009, a study by The Network Advertising Initiative showed that behaviorally-targeted ads increased revenue by 2.68 times over general advertising7. There’s no reason for non-targeted advertising except to test for new markets opportunities.
“Build something 100 people love, not something 1 million people kind of like.”
The strength of your advertisement strategy will significantly dictate the leads you can generate in a fast-paced market. It is essential that you advertise based on data insights and expert analysis.
A statement credited to the legendary Henry Ford is quite to the point:
“Stopping advertising to save money is like stopping your watch to save time.”
Small businesses demand a fully hands-on approach. It can be tricky for owners or decision-makers to monitor data insights and skillfully make vital market decisions.
Outsourcing this vital role to companies or hiring consultants with incredible tools for analyzing market trends and recommending the best market decisions will be one of the best decisions you could make.
- Patrick McKenzie, Kalzumeus (online), “Doubling SaaS Revenue By Changing The Pricing Model” Published 2012-08-13, Link accessed on 2021-12-06. https://www.kalzumeus.com/2012/08/13/doubling-saas-revenue/
- Various Authors, McKinsey&Company (pdf, online), “Marketing & SalesBig Data, Analytics, and the Future of Marketing & Sales” Published March 2015, Link accessed on 2021-12-06.
- DOE, Global Marketing Professor (online), “Apple’s Pricing Strategy,” Published May 08, 2021. Link accessed on 2021-12-06. https://globalmarketingprofessor.com/apples-pricing-strategy/
- Michelle Peterson, UxPA Magazine (online), “UX Increases Revenue: Two Case Studies,” Published June 2007, Link accessed on 2021-12-06. https://uxpamagazine.org/ux_increases_revenue/
- Fred Reichheld, Bain & Company (pdf, online), “Prescription for Cutting Costs,” Dateline undisclosed, Link accessed on 2021-12-06. https://media.bain.com/Images/BB_Prescription_cutting_costs.pdf
- Chick-fil-a, eCommerce portal of the restaurant chain, Dateline irrelevant, Link accessed on 2021-12-06. https://www.chick-fil-a.com/
- Jack Loechner, Media Post (online), Center for Media Research’s daily Research Brief (column/commentary), “Behaviorally Targeted Ads Yield Twice The Revenue and Twice the Converts,” Published April 07, 2010. Link accessed on 2021-12-06. https://www.mediapost.com/publications/article/125477/behaviorally-targeted-ads-yield-twice-the-revenue.html
- Twitter Profile of Brian Chesky, co-founder of Airbnb, Link accessed on 2021-12-06. https://twitter.com/bchesky
- Hamish McKenzie, Pando Monthly (online), “Airbnb’s Brian Chesky: Love is all you need,” Published January 10, 2013. Link unavailable. Cached version accessed through Wayback Machine (Internet Archive) on 2021-12-06. http://pandodaily.com/2013/01/10/airbnbs-brian-chesky-love-is-all-you-need/