COVID-19 has been a system shock to marketers everywhere. Organizations have had to ditch their existing plans as they find that they’re no longer relevant, and businesses must change the way they operate. In situations like this, it can be easy to get bogged down by tools claiming to save your efforts with all buzzwords and no substance. Marketers are no strangers to buzzwords — micro-influencers, anyone? — but sometimes there are real, valuable truths behind the jargon.
AI (and by extension, machine learning [ML]) may seem like something the technical teams in your company use, or something limited to a small part of the overall marketing stack. This may lead you to dismiss it out of hand (after all, how many tools in your stack claim to be “AI-powered”?), but this is a mistake. Today, as COVID-19 continues to render all your old marketing assumptions and data useless, relying on old analytics means falling behind. To avoid becoming irrelevant as consumers’ priorities change, you need more than a BI tool. Instead of focusing on being data-driven, you need to take it a step further and become data science-driven. The question is, how?
Your marketing data is valuable insofar as you can get insights from it. Collecting it is nice, and analyzing it is even better. However, if you really want to get the most out of it, it’s critical to find the right tools to give you answers you need and help you stay ahead of your problems and uncertainty. Instead of building a new data science team, however, data science-as-a-service (DSaaS) lets you outsource the technical stuff and focus on building your marketing strategy.
Data science (and therefore DSaaS) can quickly take your data and give you better predictions and forecasts for things like lead scoring, customer lifetime value and churn, and which customers to focus on. More importantly, it can take your internal data and enhance it with thousands of external data sources to boost your marketing models and give you better results with a much broader scope.
Here are just a few examples of how DSaaS can help:
One of the biggest sources of data you have is the ads you run on platforms like Google’s AdWords, which gives you IP addresses, search terms, cost-per-click (CPC), location, and even device used. This may seem like surface-level data, but you can combine it in creative ways with data from social media, and even users’ hobbies, to find new insights that can reveal the best way to target users, the right blend of keywords to use, and even the best time of day to target your users.
Despite rumors of its demise, direct mail remains one of the most powerful methods of reaching your audience — if you do it right. However, this high-reward strategy is also high-risk, and throwing money at it without some way to improve it is simply, well, throwing away money. To get the most out of it (and get the highest response rate possible), simply using previous mailing lists isn’t enough. Using data science can help you combine your recipients’ contact information with geographic and demographic data, information about previous spending and interests, and even contextual information that can boost your responses and your bottom line.
Static websites are so 2010, but making dynamic and engaging user experiences is still easier said than done. Customers today demand personalized experiences when it comes to online shopping and browsing, but it’s hard to determine who wants what simply by checking who’s been on your website. By combining data you get from your website and machine learning tools, you can better segment your audiences with geospatial, demographic, and even economic data to offer the right products, experience, and services at the right time.
Imagine you work at an online lender, and the company already uses a risk model to determine whether someone will default on their loans or not. Instead of simply emailing and direct mailing everyone who applies for a loan, you can combine your efforts with your risk team, and focus your efforts toward those customers and applicants who are more likely to repay their loans. This gets you a better ROI for each marketing dollar you spend and increases your customers’ lifetime value in the process.
In the end, it’s all about how you can deploy your data and get the answers you need without wasting weeks finding them. Using data science as a service can shorten your discovery cycle and empower your most ambitious marketing strategies by giving you the insights you need, based on the best available data.