Modern customers are more empowered than ever. Your potential customers are aware of the many options available today–other than you. They are also enthusiastic about sticking with brands that illustrate personalized offers and messaging. Is your brand nurturing such long-term relationships?
Those are just two examples.
Big data for lead generation is helping smart marketers, and sales teams fulfill the modern customer’s needs and in several powerful ways. You can always visit oxylabs if you would like to learn more about harnessing data gathering tools to make your sales skyrocket!
In this quick guide, you’ll discover 15 ways big data can improve lead generation for smart brands in 2020 and beyond.
1. Lead enrichment
Big data can help you to know your leads on a deeper level.
For example: instead of relying on only third-party market research, you can use your brand’s website analytics, mobile app usage, and social media interaction data to learn more about them. That way, you can confidently and accurately enrich the data you already have on your current customers.
That way, you can know how to attract the leads with more success and predictability than before.
2. Improving buyer personas
To meet your ideal customers’ needs, you need to know more than their gender, age group, and income level.
You’ll also want to know factors such as what they individually treasure and what it is about their job that keeps them up at night.
That way, you’ll know how to meet them half-way through their solution search with just the right solution at hand. Timely. Convenient. Converting.
With that information, you can create rich customer avatars that help you create the right messages for attracting warm leads.
3. Hyper-personalizing the lead experience
A 2018 Accenture and Retailers Industry Leaders Association (RILA) survey showed that 63% of consumers wanted to receive personalized recommendations from retailers.
A good 64% were willing to freely share their data for exclusive deals, coupon codes, and loyalty points.
4. Segmenting an audience to know your ideal customers
Big data tools can bring together first-hand data from a lead’s calls, chat messages, product inquiries, browsing history, price preferences, and more.
When you analyze that data, it can help your brand know what your ideal customer wants and needs from a specific product or service.
You do all that without asking the lead too many direct questions or breaking GDPR privacy regulations.
5. Enhance your website for better customer acquisition
You can learn a ton from leads’ behavior on your website.
You can see which pages a specific lead browsed, how long they stayed on it, and where they clicked immediately before or after.
If you have a chatbot installed, you can pop it up, requesting the lead to ask you any questions they may have.
After breaking the ice with such a lead, you can help them find what they may be looking for or a similar product or service you offer.
6. For gauging market risk
Modern marketing tools can help you to avoid significant losses.
For example, you can easily set up a Coming Soon page. Potential customers can pre-order an item, custom-build a product, or tell you what they’d love to see in the final product before you start making it.
That is a smart lead generation and risk mitigation strategy that crowdfunding sites such as Kickstarter use for untested business ideas.
7. To do resourceful competitor analysis for lead generation
A key aspect of big data is gathering business intelligence.
A top competitor analysis tool such as SEMRush can help your brand see what the competition is doing to attract qualified leads so you can, too.
A good competitor analysis strategy can also help you lower your cost of customer acquisition. Then, you can direct funds you would have spent in persuading cold leads elsewhere in the core of your operations to boost growth.
8. Learn relevant demographic trends
Don’t use guesswork to create your brand’s marketing message and brand personality.
Instead, use big data analytics based on your target customers’ digital footprint. Use it to know the essential things, places, attitudes, fears, and aspirations they associate with.
Then you can ingrain the most relevant of those in your marketing material to create compelling messaging that attracts ideal leads to your pipeline.
9. Lead nurturing
Combined with artificial intelligence (AI) for marketing, big data can help you create hyper-personalized sequences based on what a lead does online.
It could be on your website, mobile app, social media page, third-party publication, or on a standalone landing page.
Based on where the reader (or viewer for video content) clicks next, you can understand which stage a particular visitor is on their buyer journey. Not annoy readers with erroneous results, according to Gartner.
Then you can display relevant content such as content upgrades, free resources, and special offers to persuade them to take the next step along that funnel.
10. Predictive marketing
Based on all the data you may have collected on a lead, you can become better at anticipating their behavior.
So, you can use Uplift Modeling to attract leads with similar needs, predict purchase objections, and prepare solutions so you can increase the likelihood of a purchase.
Are you in e-commerce? Use the market basket method mentioned in Smartbridge to combine products/services your target customers tend to buy together. That will successfully attract and convert leads to customers fast.
11. Doing proper lead scoring
Finding good-fit customers can be the difference between a successful campaign and splashing money on people that will never help you recover your investment.
But using big data programs will help you to consolidate the data into actionable information you can use to generate leads continuously.
And not just any leads.
But the quality of leads that are interested in buying from you because they are an excellent fit for your product/service, price point, and more.
12. Fuel profitable marketing automation
Big data has and continues to power marketing automation trends that are helping smart brands to create powerful databases as WebEngage aptly puts it.
The most advanced databases are both self-learning and able to personalize content displayed to specific customers based on their online behavior on your digital platforms.
Still, significant data advances are now able to show your marketers and salespeople where in your funnel prospects are dropping off. You can streamline that to help leads advance to checkout.
13. Proper leads attribution in a multi-channel marketing digital world
Potential customers now have a multitude of touchpoints to reach you or representatives of your brand.
You’ll want to meet them there. But sifting through clouds of raw data from several touchpoints such as your blog, several social media pages, and website can be overwhelming.
Better, you can tell which marketing channels are bringing in the most ROI. So, you can invest more funds in the profitable ones and cut spending on channels that are draining your marketing budget with little to show for it.
14. A/B Testing Different Marketing Techniques
Measuring the effectiveness of a campaign is key to knowing what works and what needs to change. Split testing is a gem of big data technology.
You can use A/B tests for purposes such as optimizing your pricing strategy and gauging the viability of trends.
You can split test your marketing copy, landing pages, and other assets to see which ones your potential customers click with the most. That way, you can direct your efforts and resources to what’s working and skip expensive guesswork.
15. Inform product improvement
Big data helps smart brands to use first-hand feedback from real people to improve their products or services continuously.
Big data analytics can help you find valuable insight in a sea of noise and fluff responses. That can help your brand to address customer preferences and set you ahead of your competition in the marketplace.
And that’s what you want.