Search data is isolated in too many companies and inaccessible outside of the search engine optimization team, which limits its reach, impact and ability to drive business success.
It’s time to rethink how you use search data.
In this article, you will learn three practical ways any company can remove the shackles from their search engine marketing records and drive business-critical decisions in a more meaningful and evidence-based way.
1. Formulate a clearer, broader picture
Data is often in silos or in different data sources.
The list of options for marketing and business analysts is endless.
The first step in making your data picture clearer is removing the barriers to integrating your business information sources and creating a larger and more meaningful data ecosystem.
There are many ways to get a more complete and clear data picture for your business and the ways typically fall into two areas:
- In-house resource for technical development and data science able to bring together, process, optimize, refine, access and provide insights from a plethora of data acquisition tasks.
- Outsource this requirement, most likely to a marketing or insights agency.
There will be a variety of logics behind the option driving you forward, but in either case, an important outcome should be:
Simple, authoritative access to a broader data ecosystem that provides meaningful, evidence-based insights to help you make more effective decisions in all critical business functions.
Effective data centralization is key and forms the basis for everything that follows.
From data processing and integrity to end users, actionable data insights and much more, including automation.
Work with Apollo Insights as a prescriptive data and marketing platform.
Whichever solution you choose, it is important to consider the key results required, such as:
- Ability to scale actions from data.
- Accelerate data-driven decision making.
- Process automation.
- Data simplification and access.
- Broader data image (depth, accuracy and scale).
- Trends, analysis and performance forecasts.
- Prescriptive measures from existing, new and changing data sets.
Many positive business outcomes can follow from larger useful datasets.
2. Real-time unbiased decision making
The goal of evidence-based decision-making is often both to find out something you didn’t know and to confirm and verify that the judgments you made are the correct ones at the time.
Too often people seek verification of data but forget to be open-minded about what the data is telling them.
This is a major oversight.
As a viable business operating in any competitive environment, you need to understand your audience and their changing behaviors, wants, needs and vulnerabilities.
You also need to understand how the possibilities change.
Acting first can bring you many competitive advantages. The ability to change focus, change focus and take action sooner resides in your existing data.
3. Intelligent automation
I would estimate that intelligent automation through areas like robotic process automation can reduce the unnecessary manual labor involved in repetitive tasks from anywhere to more than 70-80% of a marketer, analyst and related subject in the workplace.
Robotic Process Automation is the technology that enables anyone today to configure computer software or a “robot” to emulate and integrate the actions of a human interacting in digital systems to carry out a business process.
In particular, the purpose is not to remove people from key roles, but to maximize their value in a way that requires their expertise and specialization.
This is achieved through:
- Removing and reducing process-controlled activities that are repetitive and, in most cases, are more appropriate for a computer program than a human.
- And giving them the ability to spend a lot of their time using the data instead of recombining and mining the data.
Marketing is a perfect example of this. A typical marketer uses 20 to 50 separate analysis packages, crawling software, insights tools and office packages to get to a stage where the experiential and technical work can even begin.
Additionally, the marketing / data / analyst is expected to already know what they are looking for. They are expected to have at least one clear hypothesis to test.
And before they know the right data sources, manual recombination and research that they need to do before they can begin meaningful activities.
Just the thought of this process is tiring, stressful and demotivating. Imagine this being replicated on every member of your team and across the company, plus the associated inefficiencies, time delays and missed opportunities that this means.
- Prioritize where intelligent automation can bring the greatest business, commercial and cultural benefits.
- Centralize control, manage spending and keep momentum going over the long term.
Smart automation can take many forms. In fact, you’ll be doing some of this by having a proactive team that just wants to get more value in less time and spend more time implementing insights instead of sourcing them.
Where you start with the information architecture depends on your business goals and the current state of affairs.
However, normally I would expect this to include:
- Repetitive tasks better suited for computers or robots.
- Time-saving automation that allows you to scale.
- Business-critical insights that put you at a competitive disadvantage if you don’t act early enough.
- Instant understanding of the audience to position your brand at the forefront of the information or education and evaluation process.
- Unnecessary administration.
- New product and service options.