Data paralysis is a real problem. The proliferation of martech tools and marketing touchpoints has created a wealth of data which, while a boon for businesses, can also present challenges when it comes to data management, analysis, security, and consistency.
A 2018 survey of nearly 400 marketers by Fospha Marketing found that a third of respondents believed their company analyzed less than 20% of all consumer data available to them.
The same survey found that only 33% of brands believe their current measurement perform accurate attribution of all media and data.
The problem of too much data is exacerbated by the proliferation of martech tools that companies use to obtain information from consumers. To combat this, marketers have begun adding even more tools to their tech stack.
The Fospha survey found that businesses use an average of 7 technologies just to extract insights from their data.
While CRMs, CX software, marketing measurement and analytics platforms, and other data-driven technologies have the potential to deliver comprehensive customer insights, they don’t always paint a clear picture of your customers’ needs or buying journey.
But as the martech landscape grows, new tools—many of them AI-driven—have emerged to help businesses automate the task of making sense of data.
In this post, we’ll cover five solutions that can help marketers overcome data paralysis by automating and streamlining the process of collecting, cleaning, managing, and analyzing customer and business data.
Bad data is expensive, with one study estimating the cost at roughly $3 trillion per year. It’s common for datasets to contain formatting errors and inconsistencies.
Data that’s outdated, riddled with errors, or incomplete cannot reliably be used for machine learning. It can also lead to spending an inordinate amount of time following up on poor quality leads or missing opportunities due to having incomplete or incorrect contact information.
Cleaning data is necessary, but time consuming, so what tends to happen is that the bulk of the data collected by CRMs is not usable. Beyond the vast amount of time and resources required to manually unify and cleanse data, there lies another big problem—human error.
Happily, there are tools like Insycle that address the issue of bad data. Insycle integrates with a variety of data-driven apps including HubSpot, Mailchimp, Marketo, Pipedrive, and Salesforce (among others) to fix common data quality issues automatically.
The tool performs a variety of data cleansing tasks including bulk updates/deletions, merging duplicates, data formatting for consistency, and data standardization/cleansing.
Insycle writes on its website: “Low quality data harms marketing personalization and automation, hinders sales teams who need reliable context for conversations with prospects, and impacts the customer experience throughout their lifecycle.”
Consider that just 35% of a sale’s rep’s time is spent selling, with the remaining 65% spent on administrative tasks such as data entry, company meetings, and other non-sales related tasks.
To maximize the time spent on following up with qualified leads (a key selling activity), reps must turn to the customer and prospect data they have available to them from a variety of sources such as CRM systems, ad campaigns, and call centers.
This can be overwhelming. Let’s face it, sifting through large quantities of unqualified leads or trying to manually match leads to the most appropriate accounts can cause data paralysis.
Tools like LeanData automate the process of lead routing and matching, enabling your sales team to focus on the most qualified leads and accounts.
LeanData’s technology includes a suite of tools designed to route leads, contacts, accounts, and opportunities to the appropriate person or department within your organization.
LeanData Lead Flow Dashboard—source: LeanData
“There’s a point companies reach in their growth journeys where manually managing hard-earned prospect and customer data is simply unsustainable,” said Evan Liang, CEO of LeanData. “LeanData’s platform intelligently automates this process, enabling these companies to match the right data, route to the right seller, and take the right action, every time — so their lead-management processes scale to support their business as it grows.”
There is, perhaps, no greater source of data paralysis than in the analysis of operational data used for business insights.
If done manually, analyzing data for the purpose of making business decisions and improvements requires many steps that may include exporting and combining data from different sources, de-duping data so that it can be appropriately charted and analyzed, and entering certain data points by hand.
All this manual labor must occur before any analysis can be made or actionable insights determined. Add to this that data is constantly being generated from a variety of internal and external sources, and the task of reviewing data in any ongoing, consistent way is impossible without the help of automation.
Enter IBM’s Watson, a sophisticated AI platform that helps businesses, “predict and shape future outcomes, automate complex processes, and optimize employees’ time.”
Watson is an enterprise-level tool designed to manage extremely high volumes of data. Its suite of applications includes solutions for IT, customer service, risk/compliance, and financial data analysis.
There is no easy way to summarize what Watson can do for businesses other than to say that it is the ultimate platform for helping enable data-driven business decisions.
Illustration of Watson’s “AI Ladder”—source: IBM
Delivering optimal customer experience is a data-driven exercise. Without a plan in place to optimize customer communication and improve your interactions with customers regardless of touchpoint, you’ll have a difficult time reducing churn rate and keeping your customers happy.
Medallia is an AI-powered experience platform that helps companies automate the process of improving customer experience by detecting patterns, anticipating customer needs, and predicting behaviors using, you guessed it, customer data.
Medallia does this in a variety of ways via a robust suite of tools that capture signals from SMS conversations, speech/voice interactions, digital touchpoints like websites, IoT devices, social media, and pretty much any place—online or off—that you interact with your customers.
Example of how Medallia helps businesses capture signals—source: Medallia
In addition to capturing signals from multi-channel touchpoints, Medallia uses data to analyze and predict outcomes based on the signals its tracking.
This enables businesses to take action via a suite of products like Zingle, a tool that streamlines the check-in process for hospitality businesses like hotels and Strikedeck, a customer success platform that facilities upsell/cross-sell opportunities by driving customer trust and loyalty.
While each of the above tools addresses this problem of data paralysis by automating some or all of the steps involved in collecting, managing, and cleansing data, sometimes you just need a simple tool to help analyze data for the purpose of obtaining high level insights.
There are a proliferation of low cost and free tools that can help you overcome data paralysis without making a major investment in time or money.
One of these is Google Data Studio (GDS), a free tool from Google that enables businesses to create visual dashboards by pulling data from commonly used platforms such as Google Ads, Google Analytics, BigQuery, and many more.
GDS pulls data from platforms like Google Analytics, then automatically turns it into easy-to-understand charts, graphs, and tables. The tool requires almost no setup and is easy to connect to your existing accounts.
It supports over 200 integrations (Google calls them “connectors”) for popular platforms like Adobe Analytics, Adroll, and Bing Ads. Note: not all integrations are free.
Here is an example of a Google Data Studio report that uses Google Analytics sample data to provide a quick snapshot of website activity.
GDS dashboards are updated in real time and you can change the date range via a drop down menu, eliminating the need to manually export reports and/or update spreadsheets and graphics. Once your dashboard is created, you’re basically done.
The tools listed here are merely examples of technologies that exist to help you manage and leverage your data. Some of them, like Medallia and IBM Watson, are enterprise-level tools that come with hefty price tags.
Don’t let this dissuade you from looking for solutions that fit within your budget and business type.
After all, there are over 8000 companies that fall within the 2020 martech landscape, with new technologies emerging every day. If your business suffers from data paralysis in any capacity, there is likely a tool on the market that can help you leverage your data more efficiently and effectively so that you can continue to drive growth.
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