6 Key Retail Challenges Technology Can Solve For Retailers

The retail industry serves a customer base that is more informed and empowered than ever before. This has had a profound impact on customer shopping habits as they take advantage of both established and emerging technologies. The flood of data coming from digital channels create as many opportunities for retailers as challenges. A key to success is to understand them and to put to work modern solutions able to manage an omnichannel experience, learn from big data and convert it into new revenue streams.
Value-oriented customers and a growing population of digital natives equipped with smartphones, Personal Assistants and wearables, expect seamless, personalized, and experiential interactions.
Fundamental shifts also relate to the ways consumers access and browse the digital space with more than 50% of all search queries to be voice and image activated while using 8 billion devices just 3 years from now, according to Statista. Each user equipped with at least 6 different devices will expect retailers to follow their tracks.
By the way, less then 4% of current businesses are voice search ready as Uberall found out in their study. To be a factor in retail, you have to keep up or get pushed aside by someone who can meet customer demands better. With the current health and economic situation unfolding, expect even more profound, permanent and accelerating shifts in consumer behaviors and buying patterns as they switch preferences to online channels for provision of products and services.
Key considerations for retailers:


With goldfish-level attention spans of 8 seconds getting even shorter for majority of content, retailers struggle to maintain effective and consistent communication with their customers while at the same time making over 10.3 billion product and pricing decisions every day. Unfortunately, only one quarter of customers are satisfied with retailer efforts and the rest leave without making a purchase. Also, heavy promotions don’t make such a difference for customers or retailers: more than two-thirds of promotions prove to be unsuccessful as various reference sources state.
The pending economic downturn may further impact these statistics, pushing even more affluent segments of customers to become true value seekers, switching to basic offers with low price tags and even deeper discounts. The resulting fiercer competition in the crowded online space will call for unprecedented digital intelligence among retailers. It will also call for an acceleration of the investments in the supporting analytics and tech stack with a much shorter time- and value-to-market.
Key considerations for retailers:


To add to such a complex picture, retail chains are also fighting internal battles which again may further spiral upwards in the outbreak. These battles are related to deeper margin erosion, unpredictable demand, shortages of supply, siloed processes and outdated systems, all topped with a constant need for tech savvy talents equipped with relevant tools.
Even pure eCommerce players, natives in the digital world and having much higher visibility into their customer data gathered from online and mobile touchpoints, face the same challenges:
1. Getting and maintaining a single customer view blending online and offline touchpoints at physical and digital locations.
Only 31% of retailers have invested in a Customer Data Platform, while another 46% are considering such an implementation, according to one of the reports on CDP.

Even more interesting, 29% of retailers decided not to integrate any system, thus preventing any level of customer view unification.
2. Mapping and properly understanding customer intentions along the customer journey
Stepping into the shoes of customers and seeing the world from their eyes is a huge challenge for most retail players. Some mistakenly take a few touchpoints from interactions with their brands on their own sites as key indicators for the entire customer journeys. But a pool of various research estimates that even leaders might get up to 50% visibility, while the rest are left with an even more limited picture.
3. Activating data-driven customer insights to delight and retain their customers by offering great individualized experiences and offers at each touchpoint
According to an HBR study, 62% of companies claim they invest in real-time analytics driving contextual experiences across their customer journeys. At the same time – as indicated by Gartner – only 12% of consumers recognize customized assistance efforts from brand. And even top-class examples reach the level of 60% of the overall customer satisfaction from end-to-end orchestrated experiences, as McKinsey study points out. Retailers also recognize this challenge – only 22% are satisfied with their ability to translate data into relevant insights at the right time. Surely there is a big gap for retailers to close.
4. Monitoring in real time and analyzing against targets and ROIs to drive next profitable decisions based on insights
Despite the obvious value of using real-time analytics to provide actionable customer insights driving more revenue, only 16% of companies claimed they are very effective at delivering real-time interactions across various channels and 30% indicated they were not effective at all, according to the HBR study. And with 79% of companies saying that such capabilities will be extremely important in 2020, it’s time for retailers to redefine their approach and put greater effort into how to enable customer analytical contributions to happen.
5. Performing in the context of market and competitive propositions
90% of businesses recently reported that their industry has become more competitive in the last three years. However, our experience shows, as supported by Crayon research, that many players still use traditional desktop research methods on data discovery via browsing competitor or price comparison sites, third party or social media websites, checking world of mouth or buying ad-hoc reports from various providers of market and competitor intelligence data.
The subsequent format CI outputs in the form of slide shows of competitor profiles, reports or exec decks and battlecards also promote periodical or ad hoc usage with majority being sent through e-mail or provided in the meetings. Not many retailers are able to systematically collect and ingest data using appropriate technology to enrich their internal datasets for further usage in their decision-making processes. Clearly a long way to go in that aspects as well.
6. Planning all activities based on their potential to deliver company goals and personal KPIs which in turn may change at the speed of light (and not in line with yearly budgeting processes or quarterly reviews)
According to our insights, a whopping 73% of companies argue that they still struggle with accurate, timely and consistent reporting and monitoring of their business critical KPIs. Many versions of truths hidden in various reports and individual Excel files is another dimension of this universal KPI challenge.
There is also another crucial dimension that should not be omitted from the retail challenge discussion: security of customer data management and regulatory compliance (GDPR, CCPA or broader ePrivacy). Perhaps even more importantly, the growing bifurcation in customer wants and expectations, or the so-called privacy paradox.
Fully personalized, relevant experiences and offers versus a reluctance to share personal details and to give consent to subsequent data usage outside narrow cases related to completion of transaction or delivery of post-purchase service. Gartner predicts that by 2025, 80% of marketers will abandon their personalization efforts. This might be a huge turnaround for both retailers and tech companies using and offering personalization engines of various sorts. The prediction is related to the disillusionment in actual ROIs and poor data security capabilities.
On the other hand, the same Gartner study points out that the retailers able to personalize their messages around helping consumers to get a better deal, save time, provide new useful information or make the purchase easier and enjoy a 16% higher commercial impact. Research from BCG shows that brands able to create personalized experiences by integrating advanced digital technologies and proprietary data for customers are seeing revenue increase by 6% to 10%, 2-3 times faster than those without such capabilities.
Key consideration for retailers:


While the majority of retailers agree on this factor of critical importance, only 21% of companies claim to be successful in providing data accessibility, in other words in getting the right data to the right people at the right time. Complete the picture with only 19% of them being able to add or enrich data with new sources and the size of the challenge is evident. Those companies that got it right will be the leaders of tomorrow in providing rich and ROI –enhancing, real-time customer analytics and insight execution.
Applying advanced data science methods to retailers’ massive data sets might prove to be extremely fruitful, yielding between $400 and $800 billions of aggregated value or expressed as a revenue boost of between 3,2 and 5,7% according to McKinseyv. And as only approximately 18% of retail businesses are currently leveraging AI, again the gap is huge but there are many exciting vendors and opportunities on the market to invest in such capabilities.
Interestingly, instead of building their own data science teams and developing their own technologies outside core organizational DNA or buying standardized software of the shelf, retailers can launch a co-creation program with partners equipped with both tech and sector expertise to build solutions tailored to their specific business requirements and addressing their unique use cases while not forgoing all the benefits that SaaS and cloud based solutions bring.
For example, Synerise offers lighthouse partnership in solving retail challenges. We work together with one of the biggest retail chains in the world, addressing key pain points with cutting-edge technologies including AI. When structured right, such an approach can bring both fast time- and benefit-to-market while building internal capabilities at scale and ensuring new tech adoption between business users.
