Measurable objectives are a vital ingredient of long-term success, says Stu Neilson, Product Strategist at Rawnet…
Product strategies relate to what a brand wants to accomplish, providing context around the market they operate in and guiding an overall theme of activity that will help the business to achieve its goals and vision. Understanding how to engineer a strategy driven by data is key to driving and building long-term success. The system of measurable objectives created will work together to align teams around desirable outcomes, both for the organisation and its customers.
1. Where do brands start?
The first step is to have a clear vision of what the brand wants to achieve, replacing reactive marketing strategies with a proactive long-term plan. Start every product strategy with a discovery phase. This will involve identifying the company’s objectives, ongoing pain points and opportunities for growth. This discovery phase entails brands taking a deep dive into their customer’s journey, establishing who they are, what motivates them and their preferences, to form in-depth detailed personas. Not only does this help identify areas where organisations need to conduct further research into customers, but recognise growth opportunities within the business and marketing strategy in the future.
2. When does data come into play?
In order to create a data-driven approach while outlining the purpose and challenges, businesses need to clearly define what success looks like and how best to measure it. This could be anything from an increase in sales and generating leads, to retaining customers and growing market share. Brands need to map these goals out and include as many comparison points as possible to refer back to and see if the delivery has been successful.
A combination of data gathered from the brand’s customers, stakeholders and competitors, plus the KPIs mapped out, allows the organisation to start establishing more detailed objectives. Many marketers use Objectives and Key Results (OKRs), which ensure that there is a clear goal, along with a defined way of measuring success. OKRs can inform everything from UX, design and development to the ongoing marketing acquisition work. This ensures that all deliverables are mapped out in a way that will allow the brand to ensure that all goals have a purpose, and clearly identify what is and isn’t working with the product.
At this stage, there is also a need to identify the systems that allow businesses to report and analyse performance. Basic systems such as Google Analytics provide the required events and goals needed, moving up to a Data Studio with more customised reporting and collating different data points, before bolstering the brand’s data insights with site engagement monitoring like Hotjar. Ultimately, there is a vast number of different tools available to track insights or data, and deciding which system is the most effective is determined by what the organisation is looking to measure.
Building a brand’s data insights and analytical understanding is vital, but it’s also critical to consider where to store this information and how best to utilise it in the business' product strategy. This is often where MarTech comes in, to allow marketers to maximise automated efficiency to adopt and scale marketing efforts faster and smarter.
3. What are goal loops?
These are key to a data-driven product strategy. By regularly checking success, having all stakeholders agree and aligning tasks directly against these measures provides brands with insights and loops back, increasing long-term performance. This stage is fundamental in driving success. Sharing findings, results and knowledge on the project can help improve the decision-making process for everyone involved.
What’s more, by talking to the business’ project team and stakeholders, marketers can ensure they are happy with the progress and results, keeping them all on the same page. This also allows stakeholders to understand how the project is going to benefit the business, and leverages feedback from all areas of the organisation.
4. What if there isn’t enough data to inform decision making?
Where there is limited data availability, brands can release a Minimum Viable Product (MVP). This provides an opportunity to release a product quickly, gather some insights and fine-tune from there. Businesses can then use customer and stakeholder feedback initially before refining the strategy as the insights start to take shape. Once the data is formulated, changes can be made in a process of continuous improvement.
Now is the time for brands to begin testing the success of a new strategy. There is no one-size-fits-all solution or guideline for strategy success – every business, product and audience is different. Testing and formulating data insights is the best way to gain a concrete understanding of what is working and what needs improvement for long term business success.